AI/Data Scientist

Role Overview

• 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).

Tech Stack

• Numpy
• Pandas
• Python
• Scikit-Learn
• SDLC

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.