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.
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.
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.
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.

Requirements

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.

Benefits

Comprehensive health, dental and vision insurance*
Life and AD&D Insurance*
Financial advisory services*
Supplemental Insurance Benefits (Accident, Hospital and Critical Illness)*
Health Savings Account*
Equity shares*
Discretionary PTO plan*
Parental leave*
401(k)
Flexible working hours
Remote-first company
Paid company holidays
Free digital therapist for you and your family
*Eligibility: Full-time employees regularly working 25+ hours per week

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata sciencedata pipelinesmodel versioningmonitoringPythongradient boostingrandom forestslogistic regressionsurvival analysis

Soft Skills

team managementmentoringcommunicationcollaborationgoal settingfeedbackdevelopment opportunitiesintellectual rigorcontinuous improvementclient engagement