VP, Data Science and Analytics
Seattle, New York City, Boston, or Remote
Full Time Executive-level / Director USD 240K - 280K
- Remote-first
- Website
- @PearlHealth_ 𝕏
- Search
Pearl Health
Enabling Primary Care Physicians across America to take back control of their patients, their finances, and time — and to bet on themselves.Who we are. . .
Pearl Health is powering the future of healthcare. We help primary care providers and organizations to deliver quality healthcare to the patients who need it most, when they need it most — and get rewarded for keeping patients healthy.
Our technology, services, and financial tools enable better, more proactive care, decrease total cost of care across patient panels, and optimize performance in value-based care models for Traditional Medicare and Medicare Advantage.
We are a team of physicians and public health experts (Stanford, Harvard, Mount Sinai), technologists (athenahealth, Amazon, Meta, Flatiron), healthcare innovators (Centivo, Aledade, Stellar, Arcadia), and experienced risk management professionals (CVS/Aetna, Humana, Oscar) who believe that primary care providers are the key to addressing our healthcare system’s biggest challenges.
Since its founding in 2020, Pearl has expanded to partner with thousands of primary care providers in practices and organizations across 44 states. Our investors include Andreessen Horowitz, Viking Global Investors, AlleyCorp, and SV Angel.
The role. . .
As the VP of Data Science & Analytics (DS&A), you will be a pivotal leader within Pearl Health, reporting directly to the Chief Data Science Officer. You will lead a critical function responsible for shaping the strategic direction of our DS&A initiatives and research projects, helping DS&A leadership manage the day-to-day execution of those projects, and ensuring the delivery of high-impact solutions that drive business outcomes. This role demands a visionary leader with exceptional technical depth, a proven track record of building and scaling high-performing teams, and the ability to influence at an executive level. You will be responsible for establishing best practices and standards for the team’s research, stewarding the career development of talented managers and principal-level researchers, and fostering a culture of technical excellence and strategic impact within the DS&A organization.
What you’ll bring. . .
Strategic Leadership, Collaboration, and Vision: Partner with leadership across the company to establish and champion the DS&A team's priorities and ensure bidirectional strategic alignment. Work with these same leaders to deliver integrated, high-value, and timely solutions. Provide strategic guidance to DS&A leaders in managing complex projects, encompassing execution and critical cross-functional stakeholder alignment. Collaborate with the Chief Data Science Officer to define and evolve the team's multi-year research trajectory, identifying new opportunities and fostering innovation.
Talent Leadership: Lead, mentor, and develop DS&A managers and Principal Data Scientists, fostering their professional growth and career progression so that they can harness the energy and talent of their reports to support Pearl’s mission.
Technical Excellence & Research Taste: Cultivate and nurture exceptional research taste and technical rigor across DS&A leadership and their teams. Collaborate with the Principal Data Scientist and other senior talent in order to mentor, energize, and orient complicated and technically nuanced research.
Operational Efficiency, Quality Assurance, & Risk Management: Collaborate with DS&A leadership and the Chief Data Science Officer to establish and refine internal systems and best practices, empowering the team to maximize impact by eliminating bottlenecks. Establish and refine robust frameworks to ensure the quality, rigor, and validity of team outputs are calibrated to business impact, risk, and regulatory considerations. Ensure all standard operating procedures (SOPs) adhere to statutory compliance standards and uphold a high ethical bar.
Infrastructure & MLOps Partnership: Work closely with the VPs of Engineering and Technical Operations to envision, create, and maintain a robust, scalable, and secure MLOps environment, proactively addressing future infrastructure needs driven by research, product, and company growth.
GenAI Application & Enablement: Pioneer the application of Generative AI (GenAI) within DS&A operations to amplify team impact and serve as a model for company-wide adoption.
Organizational Development: Drive the long-term growth and evolution of the DS&A organization, including talent acquisition, retention, and succession planning, ensuring sustained capability to meet future business demands.
Executive Communication: Communicate complex technical concepts and strategic initiatives clearly and persuasively to executive leadership, investors, and external partners, influencing critical decision-making.
Who you are. . .
10-15 years of progressive experience in data science, analytics, or a related quantitative field, with 5-7+ years in senior leadership roles managing multiple teams.
Advanced degree (Ph.D. or Master's) in a quantitative field (e.g., Data Science, Computer Science, Statistics, Mathematics, Operations Research, Physics) or equivalent practical experience.
Proven track record of defining, building, and scaling high-performing data science and analytics organizations within fast-paced, high-growth environments.
Deep expertise in advanced machine learning, statistical modeling, experimental design, causal inference, and/or large-scale data processing.
A history of spearheading deep research initiatives in machine learning and analytics, with a proven ability to guide teams in delivering innovative, scalable, and production-ready models that drive significant business value.
Exceptional leadership, communication, and interpersonal skills, with the ability to inspire, influence, and collaborate effectively with diverse stakeholders at all levels, including executive leadership and external stakeholders.
Extensive experience establishing and refining data governance, MLOps, and quality assurance best practices.
Strong understanding of data architecture principles and proven experience collaborating with engineering teams to build robust data and MLOps infrastructure.
Experience in the healthcare domain is a plus.
Our Values
We are an Equal Opportunity Employer and our employees are people with different strengths, experiences and backgrounds, who share a passion for improving people's lives. Our definition of diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. We believe all of our colleague’s points of view are integral to our success, and that inclusion is everyone's responsibility and a cause of beautiful things.
We welcome candidates from all backgrounds and are committed to a fair hiring process free from discrimination and focused around problem solving, improvement, and mutual empowerment.
Compensation and Benefits
The salary range Pearl Health expects to pay for this position is between $240,000 - $280,000 per year. Full time employees are also eligible for annual discretionary bonus. Where a given candidate falls within that range will depend on a variety of factors, including, but not limited to, the candidate’s relevant skills, experience and location, labor market conditions and participation, if any, in other compensation arrangements. Pearl Health provides its employees a competitive benefit package - for more information please review our benefits page.
Agency Submissions
We are not currently working with contingency search firms. If a resume is submitted to any Pearl Health employee by a third party without a valid written and signed search agreement, it will become the property of Pearl Health and no fee will be paid, irrespective of whether the candidate is hired.
Tags: Architecture Causal inference Computer Science Data governance Engineering Generative AI Machine Learning Mathematics MLOps Physics Research Statistical modeling Statistics
Perks/benefits: Career development Competitive pay Health care Salary bonus Startup environment
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