Lead Data Scientist

Posted 3 Days Ago
San Francisco, CA, USA
Hybrid
Senior level
Healthtech
The Role
Lead development and deployment of predictive, risk-scoring, and optimization models for behavioral health using claims and clinical data. Define data science infrastructure, perform deep analytics, translate models into client-facing impact and dashboards, and lead cross-functional product and client engagements.
Summary Generated by Built In
About Onos Health

Onos Health’s mission is simple but ambitious: ensure every healthcare dollar goes toward delivering the highest quality care. Today, 30% of total U.S. healthcare spending is wasted due to ineffective care and administrative burden caused by misalignment between providers and payers.

Onos is addressing this by building the largest AI-driven healthcare data platform. Our model enables payers to make faster, more accurate decisions across their populations. By guiding members to the right care, Onos is channeling more dollars to high-quality care that drives outcomes while making healthcare more affordable.

Come join a category-defining company and transform how healthcare is managed in the U.S.

Why Onos?
  • Meaningful impact: Help fix what is fundamentally broken in healthcare

  • Direct collaboration: Work alongside experienced founders with deep healthcare and data expertise

  • Culture: Join a high-performing, transparent, and results-oriented team

  • Ownership: Significant responsibility and autonomy from day one

  • Opportunity: Play a pivotal role in building a fast-growing, category-defining healthcare AI company

The Role

We’re looking for a Lead Data Scientist who thrives in a fast-moving startup, loves solving complex problems in messy healthcare data, and wants to directly shape how payers manage care. This is a highly strategic and hands-on role at the intersection of data science, product, and clinical operations.

As Onos’ lead data scientist, you’ll own the development of our core analytics and AI models, from designing predictive frameworks to measuring clinical appropriateness and cost savings. You’ll partner closely with product, engineering, and client teams to translate data into measurable impact for health plans, driving smarter utilization, improved outcomes, and reduced waste across Behavioral Health.

What you'll be doing at Onos:
  • Model Development: Design and deploy predictive, risk-scoring, and optimization models that identify waste, inappropriate utilization, and care improvement opportunities across behavioral health services.

  • AI/ML Infrastructure: Help define and evolve our data science stack, from feature stores and pipelines to model monitoring and evaluation frameworks.

  • Data Exploration & Analysis: Dive deep into claims and clinical data to uncover trends, outliers, and actionable insights.

  • Client & Product Impact: Partner with client teams to translate complex models into clear insights that demonstrate ROI, inform payer workflows, and maintain clear, impactful dashboards.

  • Cross-Functional Leadership: Collaborate with the CEO, CPO, and engineering team to guide product direction, data strategy, and key client engagements.

What we're looking for:
  • 8+ years of experience in data science or advanced analytics (preferably in healthcare or health plans; experience with claims and clinical data strongly preferred).

  • Deep expertise in statistical modeling, causal inference, and ML (Python, SQL, and related libraries such as scikit-learn, statsmodels, PyTorch, or similar).

  • Familiarity with healthcare data standards (claims, eligibility, EHR/clinical data, coding sets like ICD, CPT, HCPCS)

  • Experience building production-grade models and deploying them in analytical or product environments.

  • Proven experience building, mentoring, and leading high-performing data science or analytics teams.

  • Scrappy with an entrepreneurial mindset: resourceful, proactive, thrives in ambiguity, and moves fast

  • Excellent communication skills an ability to translate complex data into clear business insights

  • Exceptional references from colleagues and former managers

Benefits and Perks
  • Flexible hybrid arrangement: ~3 days/week at San Francisco office (Financial District)

  • Unlimited vacation policy

  • Paid parental leave

  • Medical, dental, and vision insurance

  • Pre-tax commuter benefits

  • 401(k)

  • Significant equity as an early employee

  • Direct mentorship from experienced founders

  • Ground-floor opportunity to help build a team and culture

  • Regular team events and off-sites

  • Company-provided equipment and home office setup

We are an equal opportunity employer and 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, or disability status.


Skills Required

  • 8+ years of experience in data science or advanced analytics
  • Experience in healthcare or health plans; experience with claims and clinical data
  • Deep expertise in statistical modeling, causal inference, and machine learning
  • Proficiency with Python and SQL
  • Experience with libraries such as scikit-learn, statsmodels, PyTorch (or similar)
  • Familiarity with healthcare data standards and coding sets (claims, eligibility, EHR, ICD, CPT, HCPCS)
  • Experience building production-grade models and deploying them in analytical or product environments
  • Proven experience building, mentoring, and leading high-performing data science or analytics teams
  • Excellent communication skills and ability to translate complex data into clear business insights
  • Exceptional references from colleagues and former managers
  • Scrappy entrepreneurial mindset: resourceful, proactive, thrives in ambiguity
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The Company
HQ: San Francisco, CA
8 Employees

What We Do

There are too many reasons why Healthcare is unaffordable in the U.S, but one of the largest is waste. Up to 40% of healthcare spend is lost on inefficiencies, administrative costs, and ineffective care practices. We’re building a system that unites providers and payers with one goal: delivering the highest quality care while eliminating waste.

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