About Us

At Sprinter Health, our mission is to dramatically expand access to healthcare by reimagining the patient experience—delivered at home and powered by technology for scale.

We're building the technology and clinical services platform to make preventive, connected healthcare accessible for everyone in the US. We deliver hybrid care (in-home + virtual) backed by data products across 15+ states, serving 60%+ of the US population through major health plans and systems. With 1M+ patients and 92+ NPS, we're rapidly scaling our impact. Our team of technologists, clinicians, and operators is backed by investors including a16z, General Catalyst, GV, and Accel that have funded companies like Devoted Health, Livongo, Benchling, Stripe, Ramp, Airbnb, Lyft, Instagram, and Databricks.

We have a rapidly growing team of visionary leaders who are passionate about increasing access to care, lowering healthcare costs, and improving outcomes for patients.

About The Role 

We're rapidly growing our clinical team as we cultivate new partnerships with enterprises across the healthcare spectrum. We're looking for an experienced Registered Nurse (RN) to work as a Clinical Manager to oversee our west coast region as well as future markets in the nation as we continue to expand. 

This role will report to the Director of In Home Care and you will collaborate closely with all Clinical Managers and internal stakeholders to effectively lead the charge of the Sprinters in your assigned regions. The ideal candidate will be an experienced leader with demonstrated ability to effectively manage teams, identify and create solutions.

Clinical Operations Management

• Oversee the daily operations of the clinical field team, ensuring smooth workflow.

• Develop and implement policies and procedures to maintain high standards of care.

• Monitor patient care quality, ensuring adherence to clinical guidelines and best practices.

Staff Supervision & Development

• Recruit, train, and manage the clinical Sprinter team.

• Conduct performance evaluations and provide ongoing coaching and support.

Compliance & Quality Assurance

• Ensure compliance with healthcare regulations (OSHA, HIPAA, Joint Commission, etc.).

• Monitor incident reports and implement corrective actions as needed.

• Lead quality improvement initiatives to enhance patient safety and service delivery.

Financial & Resource Management

• Control expenses, and allocate resources effectively.

• Optimize clinical workflows to improve efficiency and reduce costs.

Patient Care Coordination

• Address patient concerns and ensure a patient-centered approach to care.

• Respond to abnormal labs, tests, vitals- assess, triage patients to ensure proper follow up care is received. 

• Implement strategies to improve patient satisfaction and outcomes.

Collaboration & Communication

• Work closely with the Clinical Manager team and cross functional teams to ensure Sprinters are supported in the field and all teams are aligned.

• Attend management meetings and provide updates on clinical operations for your market.

You will thrive at Sprinter Health if you have:

• The desire to work collaboratively with a tight-knit but quickly growing team across many different areas of the  business

• Flexibility, humility, and a sense of humor

• Excitement for working in a fast-paced startup

Experience and Skills

• 5+ years of Registered Nurse experience

• Experience in a healthcare startup or virtual management experience preferred

• Direct report management experienceProficient at working with modern technology

• Able to do extensive travel of up to 50%

• This position will be a hybrid role where you will work some days from home and others travel to various coverage regions to meet

Sprinter Health is an equal opportunity employer. We value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or other protected classes.If you're looking for a career that offers opportunities for growth, continual development, professional challenge and the chance to make a real difference in the lives of people, apply today!

Beware of recruitment fraud and scams that involve fictitious job descriptions followed by false job offers.

If you are applying for a job, you can confirm the legitimacy of a job posting by viewing current open roles here. All legitimate job postings will require an application to be made directly on our official Sprinter Health Careers website. Job-related communications will only be sent from email addresses ending in @sprinterhealth.com. Please ensure that you’re only replying to emails that end with @sprinterhealth.com.

Why Socure?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

Job Summary:

Socure is the leading provider of digital identity verification and fraud prevention solutions, using AI and machine learning to power accurate identity trust decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.

We are seeking a Data Scientist II to join our Digital Intelligence team. In this role, you will develop machine learning features, analytical methods, and production-oriented risk signals using device, network, browser, mobile, API, session, and behavioral telemetry.

This is a hands-on role for a data scientist who can independently deliver well-scoped projects, work with complex and noisy data, and partner with engineering, product, and risk teams to improve fraud detection, identity confidence, and customer outcomes. You will deepen your expertise in Digital Intelligence while contributing to models and signals used in real-world production decisions.

Job Responsibilities:

• Develop machine learning features, models, and analytical methods for device, network, browser, mobile, session, and behavioral intelligence.

• Work on scoped fraud and identity risk problems where data quality, labels, telemetry coverage, and product tradeoffs need careful analysis.

• Build features from large-scale, high-cardinality, sparse, noisy, and platform-dependent telemetry.

• Analyze signal patterns such as spoofing, emulator behavior, automation, proxy/VPN usage, low-entropy fingerprints, telemetry gaps, and device or session fragmentation.

• Design and execute validation analyses, including train/test splits, holdout checks, leakage review, drift assessment, customer impact analysis, and feature stability review.

• Use supervised, unsupervised, statistical, and heuristic approaches to identify durable fraud and identity risk signals.

• Investigate imperfect labels, delayed outcomes, instrumentation gaps, and changing fraud patterns to distinguish useful signal from data artifacts.

• Partner with senior data scientists, engineering, product, risk, and platform teams to clarify requirements, prepare data, implement features, and support production rollout.

• Contribute to model documentation, feature definitions, explainability materials, dashboards, and production-readiness reviews.

• Communicate methods, assumptions, findings, limitations, and recommendations clearly to technical and cross-functional stakeholders.

• Support junior data scientists and analysts through code review, analytical feedback, and sharing effective modeling and validation practices.

Job Requirements:

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or a related quantitative field, or equivalent practical experience.

• 5+ years of experience in data science, applied machine learning, statistical modeling, analytics engineering, or a related technical role.

• Experience building, evaluating, and improving machine learning models, features, analytical pipelines, or risk signals.

• Strong SQL skills and experience working with large-scale, complex datasets.

• Strong proficiency in Python and experience with data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar.

• Experience with distributed data processing tools such as Spark, PySpark, Databricks, or equivalent frameworks.

• Solid understanding of supervised learning, unsupervised learning, feature engineering, model evaluation, statistical validation, and experiment analysis.

• Ability to work with noisy data, imperfect labels, missing values, instrumentation gaps, and changing data distributions.

• Strong analytical judgment across data quality, feature design, model selection, explainability, and business impact.

• Experience collaborating with engineering, product, analytics, or risk teams to move data science work toward production or operational use.

• Clear communication skills, including the ability to explain technical work, assumptions, tradeoffs, and results to non-specialist stakeholders.

• Ability to operate independently on defined problem areas while seeking guidance appropriately on ambiguous or high-risk decisions.

Preferred Qualifications:

• Background in fraud detection, identity verification, trust and safety, anomaly detection, cybersecurity, risk modeling, or another adversarial data domain.

• Experience with device intelligence, browser/mobile fingerprinting, behavioral biometrics, network intelligence, VPN/proxy detection, or telemetry signal processing.

• Experience developing features from high-cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation learning.

• Familiarity with production ML workflows, model monitoring, feature monitoring, or batch and near-real-time decisioning systems.

• Experience with dashboarding, model explainability, feature documentation, or customer-impact analysis.

• Interest in adversarial behavior, fraud patterns, telemetry quality, and applied ML systems that operate in real-world production environments.

What You’ll Gain

You will work on meaningful data science problems in fraud prevention and identity verification, using high-scale Digital Intelligence telemetry to build features and risk signals that contribute to real-world production decisions.

You will gain deeper experience with device, network, browser, mobile, session, and behavioral intelligence while working closely with senior data scientists, engineering, product, and risk partners. This role offers the opportunity to grow from independently delivering scoped modeling projects toward owning broader workstreams and developing Senior-level technical judgment over time.

Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.

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