AI/Data Scientist IV
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Job Description
AI/Data Scientist IV developing AI solutions aimed at solving complex healthcare delivery challenges. Leading collaborations and implementing advanced machine learning models in a telecommuter role.
Responsibilities:
- 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.
- (8) years of experience in quantitative analytics, programming, and/or data engineering or data science.
- 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); 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).
- Strong track record of using quantitative approaches including statistics and machine learning to solve analytical problems (preferred).
- Deep expertise in one or more of the following areas with working knowledge and interest in others (knowledge, skills, and abilities).
- Familiarity with best practices in code quality, version control, and system architecture.
- Experience working with open-source frameworks such as Transformers, Langchain/Langraph or similar, REST APIs, and optimization using asynchronous frameworks (preferred).
- Advanced in SQL for feature engineering, with an ability to handle structured and unstructured data in various research contexts (preferred).
- Comfortable working with evolving data formats and tools, leveraging data management best practices to support experimentation and prototyping (preferred).
- Skilled in a wide variety of statistical analyses (e.g., hypothesis testing, experimental design, A/B testing, regression analysis, clustering, time series analysis, anomaly detection and sequence analysis) using best practices tools such as Statsmodels, PyMC, Darts, Prophet etc. to champion data-driven decision making (preferred).
- Experienced at establishing experiment tracking to manage the iterative process of developing AI solutions (preferred).
- Familiar with measuring and monitoring traditional telemetry and gen AI observability metrics to ensure the behavior and outputs of AI solutions in production (preferred).
- Proficient at ethical AI practices including explainable AI, fairness, and mitigation of bias/hallucinations (preferred).
- Familiarity with distributed computing and/or distributed databases (Hadoop, NoSQL, 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, believe it or not, 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.
- Looking for continuing education? We have tuition assistance for both undergraduate and graduate degrees.
- Employee recognition program to celebrate anniversaries, team accomplishments, and more.
- For our hybrid employees, our on-campus model provides flexibility to create your own routine with access to on-site resources, networking opportunities, and team engagement.
- Commuter perks make your trip to work less impactful on the environment and your wallet.
- Free convenient on-site parking.
- Subsidized on-campus cafes make lunchtime connections with colleagues fun and affordable.
- Participate in engaging on-site activities such as health and wellness events, coffee connects, disaster preparedness fairs and more.
- Our complementary fitness & well-being center offers both in-person and virtual workouts and nutritional counseling.
- Need a brain break? Challenge someone to a game of shuffleboard or ping pong while on campus.
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