Develop and tune generative/agentic AI solutions aimed to solve highly complex problems within the delivery of healthcare or health plan services.
Establish comprehensive tracking of experiments to manage the iterative process of building and testing models ensuring that AI solutions fulfill business requirements.
Provide statistical rigor to these evaluations via the design of controlled tests to measure the impact of changes to the solution.
Form and leverage strong collaborations with AI engineers to scale solutions for production grade performance.
Develop and implement complex agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.
Solve new business problems by reaching, designing, building, and validating complex or novel machine learning models.
Conduct feature engineering and model optimization.
Manage the complete lifecycle of machine learning models from conception to deployment while following SDLC and responsible AI practices.
Consult with senior and executive level business leaders to scope, model, and recommend AI/ML, technical, or analytic solutions to highly complex problems within healthcare.
Build and ensure consensus with stakeholders regarding the feasibility, tradeoffs, and delivery of recommended solutions.
Research, recommend, and apply causal techniques (RCT, DiD, PSM, causal graph models, counterfactual reasoning, etc.) to estimate treatment effects to quantify or validate business benefit of complex health plan activities.
Explain business impact to program owners and leadership using approaches that are meaningful to those audiences.
Partner with program owner in the promotion or publications of results when applicable.
Participate in code peer reviews and quality assurance testing.
Troubleshoot issues as they arise to solve problems independently and collaboratively.
Serve as the technical subject matter expert to establish best practices for the team and help coach the team via formal and informal initiatives.
Maintain regular contact with customers through development cycle to ensure each step of implementation tracks customer’s needs.
Lead analytics projects applying a working knowledge of Agile and SCRUM project methodologies.

Requirements

Bachelor’s Degree in Statistics, Computer Science, Programming, Data Science, or similar quantitative field.
(5) years of experience in quantitative analytics, programming, and/or data engineering or data science for Level III.
(8) years of experience in quantitative analytics, programming, and/or data engineering or data science for Level IV.
Master’s/PhD Degree in Statistics, Computer Science, Data Science or similar quantitative field (preferred).
2+ years of experience developing solutions using language and reasoning models (preferred).
Familiarity with agentic frameworks and protocols and knowledge graphs (preferred).
5+ years of experience in developing and optimizing ML solutions using Python’s core data science scientific stack (NumPy, Pandas, Matplotlib and scikit-learn) (preferred).
Familiarity with advanced model interpretability libraries (e.g., SHAP, LIME) (preferred).
Experience with open-source environments (preferred).
3+ years of experience with ML lifecycles in production contexts, including metrics definition, drift monitoring and alerting, automated retraining, etc. (preferred).

Benefits

Medical, vision, and dental coverage with low employee premiums.
Voluntary benefit offerings, including pet insurance for paw parents.
Life and disability insurance.
Retirement programs, including a 401K employer match and a pension plan that is vested after 3 years of service.
Wellness incentives with a wide range of mental well-being resources for you and your dependents, including counseling services, stress management programs, and mindfulness programs, just to name a few.
Generous paid time off to reenergize.
Tuition assistance for both undergraduate and graduate degrees.
Employee recognition program to celebrate anniversaries, team accomplishments, and more.
Commuter perks to make your trip to work less impactful on the environment and your wallet.
On-campus model provides flexibility for hybrid employees with access to on-site resources, networking opportunities, and team engagement.

Applicant Tracking System Keywords

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

Hard Skills & Tools

machine learningfeature engineeringmodel optimizationstatistical analysiscausal techniquesprogrammingdata engineeringquantitative analyticsagentic AI solutionscontrolled tests

Soft Skills

collaborationcommunicationproblem-solvingleadershipstakeholder managementcoachingindependent workteamworkconsensus buildingcustomer engagement

Certifications

Bachelor’s DegreeMaster’s DegreePhD