Lead Applied Scientist

Humana is seeking a Lead Applied Scientist to design, develop, and scale intelligent decision systems powering its Next Best Action (NBA) platform.

The ideal candidate combines strong machine learning expertise with an understanding of decision science and software engineering.

Key Responsibilities

• Design, develop, and improve machine learning and reinforcement learning models for personalized recommendations, sequential decision making, and policy learning.
• Apply decision science, operations research, and simulation techniques to formulate complex decision problems, evaluate alternatives, and improve outcomes under business and operational constraints.
• Develop and improve production ML pipelines using Python, PyTorch, Databricks, PySpark, Ray RLlib, and MLflow, supporting large-scale data processing, model training, and inference.
• Design experiments, simulations, offline evaluations, and performance metrics to assess model effectiveness, policy behavior, decision quality, and business impact before and after deployment.
• Own models and decision policies throughout their lifecycle, from prototyping and testing through production deployment, monitoring, and continuous improvement.
• Incorporate clinical eligibility, member preferences, business rules, operational capacity, and other constraints into intelligent decision systems.
• Provide technical direction on model architecture, algorithm selection, evaluation methods, engineering best practices, and system design while collaborating with data scientists, engineers, and business stakeholders.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Operations Research, or a related quantitative field.
• 6+ years of professional experience in machine learning, applied science, decision science, or related engineering disciplines.
• Strong experience designing, developing, testing, deploying, and monitoring machine learning solutions in production environments.
• Solid understanding of reinforcement learning, sequential decision making, or other advanced decision-making techniques.
• Strong Python programming skills and experience with machine learning frameworks such as PyTorch or TensorFlow.
• Experience with distributed data processing and ML platforms such as Databricks, PySpark, Ray, or equivalent technologies.
• Strong software engineering fundamentals, including software architecture, code quality, automated testing, and scalable system design.
• Demonstrated ability to translate complex business problems into analytical models and production solutions.
• Demonstrated experience owning models across the full lifecycle, including prototyping, offline evaluation, simulation, testing, deployment, and production monitoring.

Preferred Qualifications

• Experience with reinforcement learning algorithms, contextual bandits, Markov Decision Processes, or offline policy evaluation.
• Experience with operations research, simulation, or decision analysis.
• Familiarity with MLflow, Ray RLlib, Databricks, and distributed model training.
• Experience developing recommendation systems, personalization platforms, or Next Best Action solutions.
• Experience with event-driven architectures, Kafka, Redis, or rule-based decision engines.
• Familiarity with decision mapping, multi-objective decision making, and decision making under uncertainty.
• Experience monitoring deployed models and policies for changes in performance, data distributions, and decision behavior.
• Experience within healthcare, insurance, or other regulated industries.

Additional Information

• This role is not eligible for work visa sponsorship.
• Work Style: Remote/Hybrid - Preferably Boston, MA. Occasional travel to Humana's offices for training or meetings may be required.
• Work Hours: Typical business hours are Monday-Friday, 8 hours/day, 5 days/week-- some flexibility might be possible, depending on business needs.
• Very minimal travel might be required for training, meetings, and/or conferences.

Benefits

• Medical, dental and vision benefits
• 401(k) retirement savings plan
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
• Short-term and long-term disability
• Life insurance