What you'll be doing:

• Technical Leadership & Hands-On Contribution (~50%)
- Design, build, and refine machine learning models that identify members at high risk for costly MSK interventions using claims, EMR, and enriched external data.
- Own the technical architecture for Predict's data pipelines, ensuring reliable ingestion, transformation, and delivery of healthcare data at scale.
- Establish and maintain ML ops practices—model versioning, monitoring, retraining pipelines, and performance tracking.
- Conduct rigorous analysis of algorithm performance, cost curve impact, and ROI delivered to clients.
- Stay current on healthcare data standards, regulatory requirements, and industry best practices.
- Work closely and collaboratively with Sword’s Data team to ensure Predict’s work is embedded within the Tech team’s overall infrastructure and best practices.
• Team Management & Development (~50%)
- Manage, mentor, and grow a team of data scientists and data engineers.
- Set clear goals, provide regular feedback, and create development opportunities for each team member.
- Foster a culture of intellectual rigor, collaboration, and continuous improvement.
- Hire additional team members as Predict scales.
• Client-Facing Technical Expertise
- Serve as Predict's technical subject matter expert in client meetings, sales cycles, and implementation discussions.
- Translate complex data science concepts into clear, compelling narratives for non-technical audiences.
- Partner with customer success and sales teams to demonstrate Predict's value proposition and build client confidence.
- Support business reviews, QBRs, and strategic discussions with data-driven insights alongside our Health Economics & Customer Insights team.
• Cross-Functional Collaboration
- Work closely with product and engineering teams to align Predict's technical roadmap with platform strategy.
- Collaborate with health economics to validate clinical and financial outcomes.
- Partner with data access and integration teams to expand the data assets available for Predict models.

What you need to have:

• 5-7 years of experience in data science, machine learning engineering, or a related technical field.
• 2+ years of experience managing technical teams, with a track record of developing talent and delivering results through others.
• Expertise in healthcare data, particularly medical and pharmacy claims data; experience with EMR data is highly valued.
• Strong foundation in machine learning techniques (e.g., gradient boosting, random forests, logistic regression, survival analysis) and their application to real-world problems—deep learning or transformer experience is not required.
• Proficiency in Python and the modern data science stack (pandas, scikit-learn, etc.).
• Experience building and maintaining production data pipelines using tools like Airflow, dbt, Spark, or similar.
• Familiarity with ML ops practices—model deployment, monitoring, versioning, and lifecycle management.
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders and represent the team in client-facing settings.
• Based in the United States with eligibility to work without sponsorship.

What we would love to see:

• Experience at a healthcare technology company, health plan, or healthcare analytics vendor.
• Familiarity with healthcare economics, value-based care models, or population health management.
• Exposure to predictive models for utilization management, risk stratification, or care navigation.
• Experience working in a high-growth startup environment where priorities shift and resourcefulness is rewarded.
• Comfort operating in ambiguity and driving clarity for your team.

217000 - 341000 USD a year