Job Description

Description

About the Team

The Enterprise Data & Data Science organization provides centralized product, platform, and technology support for Data Science teams across Liberty Mutual. Our team focuses on enabling the development, deployment, and adoption of AI/ML solutions through shared platforms, reusable capabilities, and enterprise-scale data science practices. We partner closely with Data Scientists, Engineers, Architects, and business stakeholders to accelerate innovation, improve operational efficiency, and help deliver business value through AI and machine learning.

Description

The Director, Data Science Product Management supports the organization, prioritization, and delivery of a portfolio of data science work that enables machine learning and AI solutions across Liberty Mutual. This role develops and drives product vision, represents the voice of the customer, and partners closely with Data Scientists, Engineers, Architects, and business stakeholders to deliver measurable business value.

This role serves as the Product Owner for a portfolio of data science enablement capabilities, partnering with engineering teams to translate customer needs into prioritized roadmaps, backlogs, and delivered solutions.

This role is ideal for a candidate who combines strong data science or technical expertise with product thinking and stakeholder leadership. Success requires the ability to understand the needs of Data Scientists, evaluate technical solutions, and translate complex technical concepts into product decisions and business outcomes.

This position may be filled as an Assistant Director or Director I, Data Science based on experience.

Asst Director, Data Science Product Management: $125,300 – $176,800

Dir I, Data Science Product Management: $142,800 – $201,300

Responsibilities

• Develop and drive product vision, roadmap, and prioritization for a portfolio of data science enablement capabilities.
• Develop business value estimates and success measures to inform prioritization and evaluate outcomes.
• Represent the voice of the customer and incorporate stakeholder feedback into product decisions.
• Partner with Data Scientists, Data Engineers, Software Engineers, and Architects to support the development, deployment, monitoring, and adoption of machine learning and AI solutions.
• Explore and evaluate technical solutions that improve model development, deployment, operational efficiency, and user experience.
• Drive the development and adoption of reusable patterns and platform capabilities that enable teams to more effectively deliver data science solutions.
• Partner with cross-functional teams to identify and prioritize technical debt reduction, DevOps, and MLOps improvements.
• Serve as Product Owner for assigned capabilities, developing, maintaining, and prioritizing product backlogs aligned to roadmap objectives and customer needs.
• Partner with delivery teams to support effective planning, execution, and delivery using Agile practices.
• Lead discussions, planning sessions, and stakeholder engagements for complex initiatives.
• Communicate product plans, priorities, recommendations, and outcomes to stakeholders and leadership.

Qualifications

• Asst Director, Data Science Product Management- Bachelor`s degree in quantitative field with 5 to 7 years of related experience within insurance, actuarial, data science or technology product management. Master`s degree preferred. ACAS helpful.
• Dir I, Data Science Product Management- Bachelor`s degree in quantitative field with 7+ years, typically 10 or more years, of related experience within insurance, actuarial, data science or technology product management preferred. FCAS / ACAS preferred
• Master`s degree preferred
• Strong understanding of data science concepts, machine learning workflows, experimentation practices, and model lifecycle management.
• Demonstrated understanding of the end-to-end data science lifecycle, including model development, deployment, monitoring, and business value realization.
• Experience working directly with Data Scientists and partnering with Engineering and Architecture teams to deliver technical capabilities and business outcomes.
• Familiarity with model deployment, monitoring, experimentation, DevOps, and MLOps practices.
• Familiarity with modern data, analytics, and AI technologies (AWS, Azure, Databricks, etc.).
• Experience supporting enterprise AI/ML platforms, data science enablement capabilities, or model operationalization efforts.
• Demonstrated ability to evaluate technical solutions and translate complex data science, AI, and engineering concepts into actionable product decisions and business outcomes.
• Experience working effectively in large, complex, and highly matrixed organizations.
• Strong communication, stakeholder management, influence, and organizational leadership skills.

About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.

At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.

We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://www.libertymutualgroup.com/about-lm/careers/benefits

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran’s status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.

Fair Chance Notices

• California
• Los Angeles Incorporated
• Los Angeles Unincorporated
• Philadelphia
• San Francisco

Job Description

TL;DR – We’re seeking an Analytics Engineer to own the data foundations that fuel the GTM teams: building reliable models, shaping metrics, powering automation, and turning raw data into the insights and data products that drive Sales and Customer Success.

Why Lovable?

Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started.

We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world.

Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software.

What we’re looking for

We’re looking for an Analytics Engineer with a background in Data Engineering or Analytics Engineering who operates as a true full-stack analyst, owning everything from raw data to insights to operationalization.

You bring:

• Strong SQL and analytical data modeling skills (ideally dbt or SQLMesh).

• Experience with ELT/ETL workflows and cloud warehouses (Snowflake, BigQuery, Redshift, Databricks).

• Comfort with Python for automation and light data engineering.

• Experience with dashboards, BI tools, and self-serve analytics.

• Clear communication, collaboration, and comfort working in ambiguity.

• Nice to have: experience with AI/LLM products, instrumentation, experimentation, or early-stage startups.

What you’ll do

• Partner with Sales and CS on data and reporting needs. Translate ambiguous business questions into structured data models, analysis and actionable insights, and data-fueled products.

• Build and maintain data warehouse models that serve as the source of truth for product usage and GTM metrics.

• Model CRM data, usage data, and billing data to power Sales and CS automation, CRM enrichment, lead definition and creation, and GTM tooling.

• Design metrics, dashboards, and data UIs in Hex and Lovable for GTM leadership and teams to access and operationalize data.

• Partner with Product and Engineering on event instrumentation and schema design.

• Improve documentation, observability, governance, and data best practices.

• Contribute to forecasting models, KPI definitions, and experimentation frameworks.

• Own and improve data pipelines, ingestion workflows, and data quality testing.

You’ll thrive here if you

• Enjoy building clean, reliable, reusable data models.

• Have experience partnering closely with cross-functional GTM teams to solve real problems with data.

• Prefer simplicity over complexity in data and tooling design.

• Communicate clearly and proactively with technical and non-technical teams.

• Take ownership, move quickly, and iterate often.

• Want to help define and scale Lovable’s data foundations and culture.

• Care about the rep experience and view analytics as a product.

How we hire

1. Fill in a short form then jump on an initial exploratory call.

2. Discuss your experience in more depth during a round of interviews with us.

About your application

• Please submit your application in English. It’s our company language so you’ll be speaking lots of it if you join.

• We treat all candidates equally – if you’re interested please apply through our careers portal.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

Metronome is the leading usage-based billing platform built for modern software companies. With Metronome, companies can launch products faster, offer any pricing model, and streamline finance workflows without writing code. Our platform computes millions of invoices per billing period and is scaling rapidly to accommodate new customers, saving them hours of development time and manual invoicing and enabling them to use consumption data to better serve their customers. Our customers love our product and approach, and we’re humbled to work with amazing companies like OpenAI, Databricks, NVIDIA, Confluent, and Anthropic.

You'll be joining an experienced team that includes founders who have successfully built and sold startups before. Our founders and employees have direct experience building and scaling teams through massive growth at companies like Dropbox, Clever, and New Relic. On the back of this experience and our success-to-date, we’ve raised over $128M from leading investors including NEA, Andreessen Horowitz, General Catalyst, Elad Gil, and Workday Ventures. We’re also proud to have founders and executives of companies like Segment, Plaid, Looker, Gitlab, Confluent, HashiCorp, and Snowflake, as investors who have experienced the pain we're solving firsthand.

About the team

The Solutions Architecture team at Metronome is a technical group that sits at the intersection of sales, growth, product, and R&D. In simple terms, we own the technical aspects of the customer lifecycle between after sales and before handoff to post-implementation teams. 

As a member of the Solutions Architecture team, you’ll primarily be focused on ensuring customers successfully implement Metronome’s products and realize value quickly.

Responsibilities

• Using proficient discovery and scoping  to understand what challenges our clients face in billing, launching new products, pricing & packaging, quote-to-cash, customer experience, and related areas.
• Doing whatever it takes to support clients throughout the entire implementation lifecycle, including requirements gathering, technical design, integration design, testing, data migration, and launch. 
• Providing expert guidance to clients regarding usage-based pricing and consumption business models.
• Hands on configuration of Metronome’s system on behalf of clients
• Designing integrations between Metronome’s APIs and the clients business systems to align to Metronome best practices (including CRM/ CPQ, Payments, Taxation, ERP, Billing Providers, Reporting and Analytics tools).
• Acting as a  liaison between the field and Metronome R&D to advocate for client needs and feature requests.  
• Partnering with implementation managers and other project team members to provide visibility into progress and proactively identify risks and issues
• Building relationships with people at our client organizations, from day-to-day operators to C-Suite executives. We believe in meeting our customers in-person whenever possible. 
• Designing integrations of Metronome into prospect systems and consultatively influencing the direction of our prospects’ pricing and packaging.
• Ensuring a proper handoff to our post-implementation teams (Customer Success and Technical Support).

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Expect these engagements to be complex, deep, technical, and most of all interesting. Metronome directly influences how the internet monetizes - AI is an obvious current example - and our group is on the front lines driving this influence with our prospects. Metronome is a startup. As such, there’s a lot still to figure out and tremendous room for high-agency people to impact our direction and strategy, build processes from zero to one, and generally make a difference. If this excites you as much as it excites us, let’s talk.

Minimum requirements

• 10+ years of experience working in technical and/or customer-facing roles involving SaaS products (for example, roles like sales engineering, solutions architecture, technical account management).
• Deep knowledge of the quote-to-cash space, including integrating with or otherwise interacting with tools like Salesforce, NetSuite, CPQs, Billing, Tax, Payments, etc.
• Experience leading complex, multi-phase technology transformation programs for enterprise companies.
• Experience in fast-moving startup environments that value high agency.
• Ability to quickly learn and communicate technical concepts to technical, go-to-market, and finance stakeholders.
• Excitement for building and improving GTM playbooks, processes, and reusable assets.
• Ability to travel approximately 30% of the time (will vary depending on client needs)

Preferred qualifications

• Experience as a software engineer, product manager, or in other technical roles.
• Strong understanding of project management and program management fundamentals and principles 
• Experience working with users from one or more of the following personas: Finance/ CFO, Engineering/ CTO, Product/ CPO, Sales Ops/ CRO, and Billing Operations. 
• Experience with logs, metrics, billing, finance, or other infrastructure or financial tooling and concepts.

Who we are

About Bridge

We’re creating an entirely new payments platform, built with stablecoins, to simplify global money movement. Bridge enables faster, cheaper payments and borderless access to dollars via stablecoins. Through our APIs, businesses can send and receive funds across borders faster / cheaper vs. SWIFT and other fiat-only rails. Our virtual accounts enable international consumers and businesses to easily access, store and spend US dollars. Our payouts infrastructure enables platforms to disburse USD to anyone globally. We believe many trillions of dollars will move and settle through stablecoin payment rails. Bridge is pulling this future forward. 

We have a small team of people who have previously built financial infrastructure at some of the world’s leading companies (Coinbase, Stripe, Square, Brex, Upstart, DoorDash, Airbnb) and each and every one of them chose Bridge because they fundamentally believe that stablecoins will be a critical piece of financial infrastructure that allows for the improvement of global money movement.

What you’ll do

We are looking for a Product Analyst  to join our Data team at Bridge. You'll own the data strategy for customer experience at Bridge, spanning two closely linked areas:

• Payments quality — transaction speed, uptime/reliability, error rates, and support ticket trends across our payment rails and products.
• Product experience — how customers interact with Bridge's dashboard, onboarding flows, and other surfaces, and where friction is costing us adoption or trust.

This focus area may shift over time as the business evolves, and we're looking for someone who can adapt their scope accordingly — spinning up their knowledge of different product areas, creating new analyses and instrumentation as priorities emerge or change.

 This is a high-ownership seat: you'll be the primary data voice for your focal area, expected to identify what matters, build the pipelines and analysis to prove it, and drive decisions from insight through to shipped outcomes — with real latitude to define how you get there.

Responsibilities

• Own the data needs for your focal area end-to-end: define and refine the right metrics, build the pipelines to source them, and drive them into decisions — without needing significant hand-holding.
• Analyze payments quality signals (latency, uptime, failure/error rates, support ticket volume and themes) to identify where customers are experiencing friction and quantify the business impact.
• Analyze product and UX data (dashboard usage, onboarding funnels, feature adoption) to find opportunities to improve the customer journey.
• Design, build, and maintain robust, well-documented data pipelines and ETL processes that make customer experience data easy to access, trust, and query across the company.
• Write and maintain production-quality SQL and pipeline code in Databricks, with work version-controlled and reviewed via GitHub.
• Build and maintain dashboards and self-serve tools that let Product, Engineering, and Support teams monitor customer experience metrics without depending on ad hoc requests.
• Partner cross-functionally with Product, Engineering, and Support/Operations to translate findings into concrete product and process improvements.
• Proactively flag emerging issues or trends in payments quality or product experience before they become customer-facing problems.
• Continuously improve data quality, documentation, and tooling for your focal area as Bridge's product and scale evolve.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 6+ years of experience as a data analyst or in a similar analytics role, ideally at a payments, fintech, or high-growth technology company.
• Excellent SQL skills, with experience querying and modeling data in a modern warehouse/lakehouse environment (e.g., Databricks).
• Hands-on experience building and maintaining data pipelines and ETL processes, and comfort working with version control (GitHub) as part of a technical workflow.
• Strong analytical and diagnostic skills — able to independently investigate a problem, identify root cause, and turn findings into a clear recommendation.
• Experience building dashboards and visualizations that communicate insights clearly to both technical and non-technical stakeholders.
• Demonstrated ability to work independently, take ownership of a focal area, and manage multiple concurrent priorities with minimal oversight.
• Strong written and verbal communication skills, with the ability to explain technical or data-driven findings to non-technical audiences.

Preferred qualifications

• Experience analyzing payments data specifically (transaction quality, uptime/reliability, support ticket trends) or product/UX data (onboarding, dashboard engagement, funnels).
• Programming experience (e.g., Python) and familiarity with data manipulation libraries (e.g., pandas).
• Experience working in a fast-paced startup or high-growth environment where priorities and scope shift with the business.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Accounting Team is responsible for understanding and telling Stripe’s financial story and shaping our collective understanding of how Stripe is performing as a business. Our primary focus is maintaining a well-controlled environment that effectively supports corporate governance, financial reporting and disclosure requirements. We advise and enable Stripe to grow – supporting all products at Stripe, consulting on accounting implications and supporting teams’ ability to make informed strategic decisions. We operate in a fast-paced environment and collaborate significantly with cross-functional and international teams.

What you’ll do

Our Accounting team is seeking an innovative embedded technical resource to help us scale for the future, in a fast-paced environment that’s growing rapidly. You’ll leverage your accounting, artificial intelligence (AI), and technical expertise to build intelligent solutions that enhance Stripe’s accounting capabilities. You’ll develop AI-powered tools and models, autonomous agents, and data products that automate complex workflows and provide actionable insights within a framework of financial reporting control. Working at the intersection of artificial intelligence, accounting, and product development, you'll collaborate with engineering and finance teams to deploy cutting-edge AI applications that scale with Stripe's growth and support our mission of increasing the GDP of the internet. 

Responsibilities

• Apply your accounting and finance domain expertise to identify, explore, and prototype high-impact opportunities where AI can solve complex accounting challenges 
• Build using AI-powered tools and artificial intelligence solutions to automate accounting workflows, enhance controllership, and scale our operations
• Design and deploy autonomous AI agents using frameworks that can reason, plan, and execute complex multi-step problems and enhance decision-making processes through understanding risk and maintaining effective financial reporting controls.
• Ship and maintain interactive data products and self-service analytics tools using SQL and Python frameworks (data visualization and dashboards, low-code application building frameworks) that provide real-time insights and actionable intelligence
• Work across Accounting and partner teams to uncover efficiency opportunities, including AI use cases, document requirements, and translate complex financial workflows into well controlled technical solutions
• Partner with Accounting and SOX teams to assess and develop an effective internal controls approach to AI-based accounting solutions

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of relevant experience, with at least 4+ years of experience in accounting related or adjacent roles (e.g. finance systems, process improvement) 
• B.A. or B.S degree in Accounting, Finance, Finance Systems or Information Systems
• Fluency in U.S. GAAP
• Advanced proficiency in SQL, including writing complex queries, using CTEs (common table expressions), window functions, and joins for data analysis and pipeline logic
• Familiarity with modern data tools (Python, Databricks, ETL/ELT processes, data pipelines) and coding with AI assistance
• Comprehensive understanding of AI fundamentals and experience with emerging AI/LLM tools, conversational interfaces, prompt engineering, or automation platforms and RPA
• Solution and results-oriented, with a focus on delivering impact in a fast-paced environment 
• Excellent communication and organizational skills, both written and verbal, with the ability to convey financial concepts to both financial and non-financial audiences
• Experience with internal controls (design, implementation and execution)

Preferred qualifications

•  Familiarity with the payments industry and fintech landscape

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

At its core, Stripe is a treasury company, and the Treasury Finance team is key to building the Global Payments and Treasury Network (GPTN). We collaborate closely with product, engineering, sales, and finance teams to create innovative solutions that enhance Stripe's financial capabilities. As part of Treasury Finance's AI and Quantitative Analytics team, you'll work at the intersection of finance, artificial intelligence, quantitative reasoning, and product development, building autonomous agents and intelligent solutions that enhance treasury capabilities and enable us to better serve and scale with the global economy.

What you’ll do

Within Treasury Finance AI and Quantitative Analytics, you'll leverage your finance, artificial intelligence (AI), and technical expertise to build intelligent solutions that enhance Stripe's treasury capabilities. You'll develop AI-powered tools and quantitative models, autonomous agents, and analytics that automate complex workflows and provide actionable insights. Working at the intersection of artificial intelligence, finance, and product development, you'll collaborate with engineering and finance teams to deploy cutting-edge AI applications that scale with Stripe's growth and support our mission of increasing the GDP of the internet.

Responsibilities

• Apply your treasury and finance domain expertise to identify high-impact opportunities where AI can be integrated with quantitative tools to solve complex treasury challenges
• Build AI-powered tools and artificial intelligence solutions to automate treasury workflows, enhance risk management, and scale our operations
• Ship interactive data products and self-service analytics tools using Python frameworks (Streamlit, Dash, Gradio) that provide real-time treasury insights and actionable intelligence
• Work across Treasury Finance and partner teams to scope AI-driven solutions that allow us to optimize and scale our most complex, data-driven financial workflows 
• Develop targeted observability and performance analytics for core treasury workstreams, providing key insights to senior leadership 
• Leverage heterogeneous and unstructured data to develop business insights and recommendations
• Collaborate with data scientists and engineers to build data pipelines, models, and infrastructure for core treasury workstreams

Who you are

We're looking for a technical problem-solver with treasury, quantitative reasoning, and finance expertise who's excited about leveraging artificial intelligence and who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Bachelor’s degree in finance, mathematics, statistics, economics, engineering, or a related technical field with 6–8 years of work experience in software development, data science, or treasury and finance roles 
• Working familiarity with financial risk and capital markets concepts
• Proficiency in Python and experience with AI/ML frameworks including PyTorch and TensorFlow
• Experience with Large Language Model (LLM) frameworks such as LangChain, LangGraph, or similar tools for building AI applications and agentic systems
• Solid understanding of AI fundamentals, including deep learning, natural language processing, and generative AI
• Results-oriented, with a focus on delivering impact in a fast-paced environment 
• Excellent communication skills for collaborating with finance, product, and engineering teams
• Highly organized, with attention to detail and the ability to manage tight deadlines

Preferred qualifications

• Familiarity with the payments industry and fintech landscape
• Experience with Databricks and cloud platforms (AWS, GCP, Azure) 
• Good understanding of development processes and best practices across engineering standards, code reviews, and testing

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

As a member of the Partner Solutions Architecture (PSA) team, you'll be responsible for providing technical guidance to Stripe’s partners. Our goal is to drive growth through co-solutioning, education and enablement with our partner organisation. The right candidate will be a critical technical liaison to the Stripe Partner Development Manager. This will involve creating comprehensive technical business plans for partners, including identifying, incubating and bringing to market service/solution offerings built on or with Stripe. A Partner Solution Architect is someone who is intellectually curious, motivated to win, open, and entrepreneurial.

What you’ll do

As a member of the team, PSAs build highly consultative trusted relationships with executives and technical decision makers in the customers' organisation to provide business and technical thought leadership, and become a trusted advisor in solving mission-critical business challenges. We architect business models with them so they drive new monetization opportunities and growth.

Responsibilities

• Work with key AI partners to build out their Stripe capabilities and solutions to grow their business and drive non-linear growth
• Develop and execute enablement plans 
• Be at the forefront of technical discussions & solution deep dives with partners on the value Stripe provides to their clients
• Engage with CTOs, engineering and other technical leads at key partners to share technology roadmaps, demonstrate the latest innovations, and define a solution strategy to expand the partnership revenue
• Communicate success internally through QBRs, etc
• Provide oversight, guidance, and assistance during the partners' sales process to ensure mutual success in joint opportunities
• Educate the Stripe sales team on key partner solutions and capabilities
• Collaborate on technical content (sample code, demos, etc.) to show partners how to implement specific use cases or best practices

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 8+ years of experience in a similar customer-facing engineering role such as solution consultant, solutions architect, sales engineer, for a global software enterprise
• Experience co-selling and co-solutioning with go-to-market partners
• Executive engagement skills and presence, with an ability to establish strong relationships with key decision makers and build credibility at all levels
• Effective group-facilitation skills and confidence in proposing and leading customer meetings to gain strategic footing and pursue opportunities
• Thorough understanding of the software development lifecycle and API architecture
• Ability to understand how a wide variety of applications such as ERP, CRM, Billing, Tax and legacy systems interact with each other in an enterprise technology ecosystem
• Has practical, hands-on experience building with top LLMs (OpenAI, Claude, Gemini) and leverage modern AI development tools like Cursor, Vercel, and Replit to move fast - additionally, you are comfortable working with scalable data platforms (Databricks, Snowflake) or major cloud ecosystems (AWS, GCP, Azure)
• Ability to continuously learn and adapt in current AI market
• Ability to define tech strategy and focused initiatives in a highly ambiguous and fast evolving domain
• Hands on prototyping, demo and customer facing (like an FDE) experience

Preferred qualifications

•  A background in payments systems and e-commerce solutions is a plus but not a requirement

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the Team

Every business running on Stripe eventually asks the same questions: What's happening with my business? What does it mean for my company? How do I reconcile my books? And how do I get my Stripe data into my own systems and apps? This is all becoming even more important in the era of AI, where merchant’s agents need the right access to, and understanding of, Stripe’s data. 

The Data Products team exists to answer those questions — at any scale, for any business. We build the products that turn Stripe's rich transaction data into understanding and action: Sigma for deep SQL-powered analytics, Stripe Data Pipeline for delivering Stripe data directly into merchants' own warehouses and applications, and databases for surfacing the right insight, in context, right inside the Dashboard.

Our users range from a founder running their first revenue report to an enterprise finance team reconciling millions of transactions across dozens of markets, to any agent working on a merchant’s behalf. What they all share is a need to trust their data, understand their business, and move fast. We make that possible.

About the Role

As the PM leading Data Products, you will own the product strategy and execution for Stripe's merchant-facing data portfolio — defining what it means for Stripe to be the best data platform for our merchants and agents. You'll set the direction across Sigma, SDP, and other data products, lead a team of PMs, and work closely with engineering, design, sales, and Stripe customers to shape how businesses access, analyze, and act on their Stripe data.

This is a high-stakes, high-visibility role. Data access is increasingly a core buying criterion for Stripe's largest customers, and the competitive landscape for data portability and embedded analytics is evolving fast. You'll need to think strategically about platform positioning, lead through ambiguity, and ship products that work flawlessly for a very sophisticated user base.

What You'll Do

• Set and own the product strategy for Stripe’s data products, defining the multi-year vision and translating it into a coherent roadmap that balances enterprise growth, self-serve expansion, and platform quality
• Lead and develop a PM team. Manage, mentor, and hire PMs; build a high-caliber team culture with strong product craft and clear ownership
• Drive revenue and retention outcomes. Deeply understand the commercial role of data products in Stripe's sales and self serve motions and build accordingly
• Define what "great" looks like for merchant data access — from schema design and query performance to delivery reliability, latency SLAs, and integrations with third-party warehouses (Snowflake, BigQuery, Redshift, Databricks)
• Partner with enterprise customers. Engage directly with Stripe's largest users to understand how they use and rely on their Stripe data, and feed those insights back into the roadmap
• Navigate deep technical complexity. Work fluently with data engineering and infrastructure teams on the underlying Reporting Data Warehouse and data pipeline architecture
• Anticipate the AI shift. Identify how AI-native workflows (agentic data access, natural language querying, automated reporting) should reshape the product surface over the next 2–3 years
• Communicate and influence broadly. Write crisp strategy docs, earn trust from senior stakeholders across Product, Sales, and Finance, and represent Data Products clearly at the leadership level

Who You Are

• 10+ years in product management, including experience leading or managing PM teams of 5+ PMs
• Deep expertise in data products. You have shipped at least one of: a BI/analytics tool, a data integration product, a warehouse connector, or a developer data API
• Strong commercial intuition. You understand how data products drive enterprise deal velocity, expansion, and retention, and you've worked closely with Sales and CS on product strategy
• Technically fluent. You can hold your own in discussions about data pipeline architecture, warehouse connectors, SQL query execution, and data delivery semantics; you don't need to write the code but you need to understand the tradeoffs
• Exceptional written communicator. You write with the clarity and precision Stripe's culture demands, from a tight decision memo to a multi-year strategy narrative
• High ownership instincts. You proactively identify what needs to happen, move fast without waiting for permission, and hold yourself accountable to outcomes
• Comfortable in a complex stakeholder environment. Data products touch engineering, enterprise sales, customer success, finance, and legal; you can align them without losing pace

Nice to Have

• Experience building products on top of or integrating with major cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)
• Familiarity with Stripe's data model and the kinds of analytics questions merchants care about (payments, disputes, revenue recognition, reconciliation)
• Background in fintech or payments — you understand the data complexity that comes with operating across hundreds of payment methods, currencies, and regulatory regimes

Why This Role

Stripe's merchants run their businesses on Stripe data. When Stripe’s data products surface the right insight at the right moment — merchants make better decisions, and they stay on Stripe. This role is a direct lever on that outcome. You'll have meaningful scope, a strong team, and the opportunity to define what world-class data access looks like for the most important businesses in the world.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Stripe processes over $1.9T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting opportunities to innovate in ML Platform at Stripe.

The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take data and build features and models from prototype to production—reliably, at low latency, and at scale. Our scope spans ML training infrastructure, model serving and deployment, feature computation and online serving, observability and monitoring, and agentic AI capabilities. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible, and user-friendly systems that substantially increase ML velocity across the company.

What you'll do

You'll serve as a technical lead across the ML Platform space and a key contributor to the evolution of the platforms that power Stripe's ML-driven products. As a Staff Engineer, you'll make decisions with a large impact on Stripe. You'll influence our investments and strategy while making our systems more reliable, secure, and a delight to use. You'll work cross-functionally with other technical staff, data science, product, and senior leadership to increase the impact of ML at Stripe.

You'll help define the long-term strategy and lead the technical direction for the next generation of ML infrastructure that powers Stripe's ML-driven products.

Responsibilities

• Take ownership of end-to-end architecture and system design for large, complex projects across ML Platform.
• Define technical direction for highly ambiguous projects, transforming complex user needs into long-lasting platform strategy.
• Design system architectures for the most challenging ML Platform problems in one or more areas, including AI and ML workflow orchestration, scalable CPU and GPU compute infrastructure, model training, LLM fine-tuning, low-latency model inference, large-scale feature stores, real-time monitoring, and LLM and agent orchestration.
• Turn high-leverage ideas into tangible, robust solutions that shape platform and product roadmap, combining technical excellence with creative problem-solving.
• Scope and lead large projects with significant business impact, driving them from requirements through design, implementation, and production operation.
• Work with ML engineers, data scientists, and product teams directly to translate their needs into functional requirements and scalable technical solutions.
• Arbitrate critical decisions that balance competing priorities while meeting latency, reliability, cost, and security constraints.
• Serve as a key engineering representative, engaging senior leaders across Stripe and advising the leadership team on key technical considerations related to the end-to-end ML lifecycle.
• Drive cross-team technical initiatives that improve ML development velocity and MLOps maturity across the company.
• Mentor and grow other engineers. Serve as a role model for designing, implementing, and operating great software systems.

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of professional software development experience, or equivalent domain expertise, with a solid background in service-oriented architecture and large-scale distributed systems.
• Track record of serving as a technical lead, with the ability to provide technical direction, lead multi-team initiatives, and mentor team members.
• Experience building and operating production ML platform in one or more areas such as model training, model serving, orchestration, or ML data systems, with requirements for performance, reliability, scalability, and cost efficiency.
• Strong product instincts and a deep understanding of the business context in which you operate.
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software engineers, product managers, and business stakeholders.
• The ability to thrive on a high level of autonomy and responsibility, and comfort operating in ambiguous environments.
• Hands-on experience using AI tools to accelerate how you work.

Preferred qualifications

• Experience building large-scale ML training, serving, or data infrastructure for machine learning use cases, such as distributed training, model inference, feature stores, real-time feature computation, and model registries.
• Experience with distributed ML training systems, accelerator-backed compute, training data pipelines, experiment tracking, and model evaluation.
• Experience rapidly developing prototypes and iterating based on user feedback.
• Experience training and shipping machine learning models to production to solve critical business problems.
• Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (e.g., tool use, multi-agent orchestration, retrieval-augmented generation).
• Familiarity with cloud services (e.g., AWS) and cloud-based AI and ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI).
• Ability to synthesize ideas across the organization while setting a compelling technical vision.
• Comfortable working with geographically distributed teams.
• Passion for side projects, open source, or self-driven technical initiatives.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Stripe processes over $1.9T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting opportunities to innovate in ML Platform at Stripe.

The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take data and build features and models from prototype to production—reliably, at low latency, and at scale. Our scope spans ML training infrastructure, model serving and deployment, feature computation and online serving, observability and monitoring, and agentic AI capabilities. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible, and user-friendly systems that substantially increase ML velocity across the company.

What you'll do

You'll serve as a technical lead across the ML Platform space and a key contributor to the evolution of the platforms that power Stripe's ML-driven products. As a Staff Engineer, you'll make decisions with a large impact on Stripe. You'll influence our investments and strategy while making our systems more reliable, secure, and a delight to use. You'll work cross-functionally with other technical staff, data science, product, and senior leadership to increase the impact of ML at Stripe.

You'll help define the long-term strategy and lead the technical direction for the next generation of ML infrastructure that powers Stripe's ML-driven products.

Responsibilities

• Take ownership of end-to-end architecture and system design for large, complex projects across ML Platform.
• Define technical direction for highly ambiguous projects, transforming complex user needs into long-lasting platform strategy.
• Design system architectures for the most challenging ML Platform problems in one or more areas, including AI and ML workflow orchestration, scalable CPU and GPU compute infrastructure, model training, LLM fine-tuning, low-latency model inference, large-scale feature stores, real-time monitoring, and LLM and agent orchestration.
• Turn high-leverage ideas into tangible, robust solutions that shape platform and product roadmap, combining technical excellence with creative problem-solving.
• Scope and lead large projects with significant business impact, driving them from requirements through design, implementation, and production operation.
• Work with ML engineers, data scientists, and product teams directly to translate their needs into functional requirements and scalable technical solutions.
• Arbitrate critical decisions that balance competing priorities while meeting latency, reliability, cost, and security constraints.
• Serve as a key engineering representative, engaging senior leaders across Stripe and advising the leadership team on key technical considerations related to the end-to-end ML lifecycle.
• Drive cross-team technical initiatives that improve ML development velocity and MLOps maturity across the company.
• Mentor and grow other engineers. Serve as a role model for designing, implementing, and operating great software systems.

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of professional software development experience, or equivalent domain expertise, with a solid background in service-oriented architecture and large-scale distributed systems.
• Track record of serving as a technical lead, with the ability to provide technical direction, lead multi-team initiatives, and mentor team members.
• Experience building and operating production ML platform in one or more areas such as model training, model serving, orchestration, or ML data systems, with requirements for performance, reliability, scalability, and cost efficiency.
• Strong product instincts and a deep understanding of the business context in which you operate.
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software engineers, product managers, and business stakeholders.
• The ability to thrive on a high level of autonomy and responsibility, and comfort operating in ambiguous environments.
• Hands-on experience using AI tools to accelerate how you work.

Preferred qualifications

• Experience building large-scale ML training, serving, or data infrastructure for machine learning use cases, such as distributed training, model inference, feature stores, real-time feature computation, and model registries.
• Experience with distributed ML training systems, accelerator-backed compute, training data pipelines, experiment tracking, and model evaluation.
• Experience rapidly developing prototypes and iterating based on user feedback.
• Experience training and shipping machine learning models to production to solve critical business problems.
• Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (e.g., tool use, multi-agent orchestration, retrieval-augmented generation).
• Familiarity with cloud services (e.g., AWS) and cloud-based AI and ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI).
• Ability to synthesize ideas across the organization while setting a compelling technical vision.
• Comfortable working with geographically distributed teams.
• Passion for side projects, open source, or self-driven technical initiatives.