Forward Deployed Security Engineer
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
Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world.
What you’ll do
In this role, you will play a critical part in safeguarding our financial ecosystem through two main pillars: actively responding to live fraud and abuse incidents as a hands-on security engineer, and serving as a key bridge between incidents and merchants to help them remediate threats, improve security posture, and protect their accounts. Leveraging your technical depth in fraud, abuse, and security engineering, you will investigate high-risk accounts, perform post-incident analyses, gather operational requirements, and drive agentic response capabilities ensuring we neutralize threats with speed and precision while elevating Stripe's product integrity function.
Responsibilities
- Respond to live fraud and abuse incidents as a Forward Deployed Security Engineer, investigating high-risk activity, neutralizing active attacks, and mitigating security risks across the ecosystem.
- Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped (Fraud Taxonomy 3.0) detection and signals enrichment to reduce uncertainty and accelerate response.
- As part of incidents, analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 to standardize threat intelligence.
- Develop, document, and execute incident response strategies, runbooks, and capabilities to continuously improve fraud and abuse detection and prevention.
- Act as a dedicated technical bridge during and after incidents to work directly with impacted merchants and customers, helping them investigate root causes, remediate vulnerabilities, and secure their accounts.
- Serve as an operational and technical liaison for legal teams, policy partners, and threat intelligence communities.
- Build and nurture strong strategic relationships across external threat intelligence communities, peer working groups, and law enforcement agencies.
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 experience leading security or fraud incident response;
- B.S./M.S. in Computer Science or equivalent experience.
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations
- Proven ability to build automated response workflows, leverage threat intelligence, and make risk mitigation recommendations.
- Strong written and verbal communication skills with a track record of driving cross-functional alignment with minimal oversight.
- Previous work with law enforcement
- Engagement in threat intelligence sharing communities
Preferred qualifications
- Broad expertise across fraud and abuse mitigation, risk management, product trust, and threat intelligence in a complex platform environment.
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges.
- Speaker or participant in external conferences or similar industry engagements
Abuse Investigator
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
Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve technical incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world.
What you’ll do
You'll play a critical role in safeguarding our financial ecosystem by investigating high-risk accounts and identifying complex patterns of fraud during incidents. You will lead incident response for product abuse and fraud events, conducting deep-dive analyses to identify root causes. By collaborating cross-functionally, you will drive improvements that enhance our fraud detection and prevention strategies at scale. Your expertise will be essential in automating response processes through agentic approaches, allowing us to safeguard merchants and neutralize threats with speed and precision.
Responsibilities
- Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped detection and signals enrichment to reduce uncertainty and accelerate response.
- As part of incidents, analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 (Fraud Taxonomy 3.0) to standardize threat intelligence.
- Lead incident root cause analyses to identify gaps in current systems and strategies, leveraging the FT3 framework, data-driven model to drive enhancements and process improvements for emerging fraud risks.
- Streamline incident response capabilities, ensuring the tooling and processes are clear, accurate and efficient
- Work cross-functionally with security, fraud and data science teams to build agentic solutions for responding to abuse incidents at scale
- Effectively communicate cross-functionally with legal and policy teams to assess and mitigate risks, while demonstrating strong problem-solving under pressure.
- Collaborate effectively with teammates, leading projects, mentoring others, and developing and championing quality standards within the team
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
- 3+ years of experience conducting incident response in security, product abuse or trust domains
- 3+ years experience analyzing large data sets to solve problems and/or building models with a behavioral approach to fraud detection
- B.S. or M.S. Computer Science or related field, or equivalent experience
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations
- Ability to communicate results clearly and focus on impact
- Ability to think creatively and holistically about reducing risk in a complex environment
Preferred qualifications
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges
Abuse Investigator
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
Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve technical incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world.
What you’ll do
You'll play a critical role in safeguarding our financial ecosystem by investigating high-risk accounts and identifying complex patterns of fraud during incidents. You will lead incident response for product abuse and fraud events, conducting deep-dive analyses to identify root causes. By collaborating cross-functionally, you will drive improvements that enhance our fraud detection and prevention strategies at scale. Your expertise will be essential in automating response processes through agentic approaches, allowing us to safeguard merchants and neutralize threats with speed and precision.
Responsibilities
- Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped detection and signals enrichment to reduce uncertainty and accelerate response.
- As part of incidents, analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 (Fraud Taxonomy 3.0) to standardize threat intelligence.
- Lead incident root cause analyses to identify gaps in current systems and strategies, leveraging the FT3 framework, data-driven model to drive enhancements and process improvements for emerging fraud risks.
- Streamline incident response capabilities, ensuring the tooling and processes are clear, accurate and efficient
- Work cross-functionally with security, fraud and data science teams to build agentic solutions for responding to abuse incidents at scale
- Effectively communicate cross-functionally with legal and policy teams to assess and mitigate risks, while demonstrating strong problem-solving under pressure.
- Collaborate effectively with teammates, leading projects, mentoring others, and developing and championing quality standards within the team
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
- 3+ years of experience conducting incident response in security, product abuse or trust domains
- 3+ years experience analyzing large data sets to solve problems and/or building models with a behavioral approach to fraud detection
- B.S. or M.S. Computer Science or related field, or equivalent experience
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations
- Ability to communicate results clearly and focus on impact
- Ability to think creatively and holistically about reducing risk in a complex environment
Preferred qualifications
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges
Security Incident Response Manager - Abuse Operations
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
Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world.
What you’ll do
In this role, you will play a critical part in safeguarding our financial ecosystem by investigating high-risk accounts, identifying complex fraud patterns, performing post-incident analyses, and driving cross-functional improvements to scale fraud detection. Building on these core operational duties, you will leverage your fraud, abuse, or product trust experience to improve incident response capabilities across Stripe by managing the entire fraud and abuse incident response process, developing response plans, leading workstreams, and serving as incident commander to ensure timely resolution. Furthermore, you will conduct gamedays to pressure-test response processes, drive proactive improvements, and help automate response workflows using agentic approaches ensuring we neutralize threats with speed and precision while continuously elevating Stripe's fraud and abuse incident response function.
Responsibilities
- Lead fraud and abuse incident response end-to-end as Incident Response Manager (IRM), coordinating workstreams, investigating high risk activity and accounts, and making actionable mitigation recommendations under pressure.
- Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped (Fraud Taxonomy 3.0) detection and signals enrichment to reduce uncertainty and accelerate response.
- As part of incidents, analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 to standardize threat intelligence.
- Develop, document, and execute incident response strategies, runbooks, and capabilities to continuously improve fraud and abuse detection and prevention.
- Partner cross-functionally with security, data science, legal, and policy teams to build agentic response solutions, refine KPIs, and deliver clear incident reporting.
- Mentor teammates, lead key incident response engineering projects, and elevate quality standards across the team.
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 experience leading security or fraud incident response;
- B.S./M.S. in Computer Science or equivalent experience.
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations
- Proven ability to build automated response workflows, leverage threat intelligence, and make risk mitigation recommendations.
- Strong written and verbal communication skills with a track record of driving cross-functional alignment with minimal oversight.
Preferred qualifications
- Broad expertise across fraud and abuse mitigation, risk management, product trust, and threat intelligence in a complex platform environment.
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges.
Integration Engineer, Metronome
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.
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.
Director I, Data Science Product Management
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
Analytics Engineer
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:
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Strong SQL and analytical data modeling skills (ideally dbt or SQLMesh).
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Experience with ELT/ETL workflows and cloud warehouses (Snowflake, BigQuery, Redshift, Databricks).
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Comfort with Python for automation and light data engineering.
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Experience with dashboards, BI tools, and self-serve analytics.
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Clear communication, collaboration, and comfort working in ambiguity.
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Nice to have: experience with AI/LLM products, instrumentation, experimentation, or early-stage startups.
What you’ll do
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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.
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Build and maintain data warehouse models that serve as the source of truth for product usage and GTM metrics.
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Model CRM data, usage data, and billing data to power Sales and CS automation, CRM enrichment, lead definition and creation, and GTM tooling.
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Design metrics, dashboards, and data UIs in Hex and Lovable for GTM leadership and teams to access and operationalize data.
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Partner with Product and Engineering on event instrumentation and schema design.
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Improve documentation, observability, governance, and data best practices.
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Contribute to forecasting models, KPI definitions, and experimentation frameworks.
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Own and improve data pipelines, ingestion workflows, and data quality testing.
You’ll thrive here if you
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Enjoy building clean, reliable, reusable data models.
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Have experience partnering closely with cross-functional GTM teams to solve real problems with data.
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Prefer simplicity over complexity in data and tooling design.
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Communicate clearly and proactively with technical and non-technical teams.
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Take ownership, move quickly, and iterate often.
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Want to help define and scale Lovable’s data foundations and culture.
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Care about the rep experience and view analytics as a product.
How we hire
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Fill in a short form then jump on an initial exploratory call.
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Discuss your experience in more depth during a round of interviews with us.
About your application
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Please submit your application in English. It’s our company language so you’ll be speaking lots of it if you join.
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We treat all candidates equally – if you’re interested please apply through our careers portal.
Product Analytics - Developer Experience, Bridge
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.
Accounting AI Solutions Lead
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
Treasury Finance AI and Quantitative Analytics, Americas
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
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