Senior Decision Intelligence Engineer – NBA

🕒 August 6

🇺🇸 United States – Remote

💵 $106.9k - $147k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 4%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Humana

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1961

🏥 Healthcare

🛡️ Insurance

⚕️ Healthcare Insurance

Healthcare • Insurance • Healthcare Insurance

Humana is a healthcare company dedicated to making a positive impact on the health of individuals, communities, and the healthcare system as a whole. With a focus on putting health first, Humana serves a diverse range of populations, including seniors and the military, providing Medicare Advantage HMO, PPO, and PFFS plans. Humana is committed to fostering a culture of belonging and mutual respect, offering competitive and flexible benefits to ensure the financial security of its employees and their families. The company prides itself on creating an inclusive workplace where everyone has the opportunity to succeed.

📋 Description

• Design, train, and improve the reinforcement learning policy powering Humana's Next Best Action platform • Design and evaluate decision-making algorithms • Instrument training pipelines • Collaborate with data and platform engineers • Ensure systems operate within clinical eligibility rules and program-specific objectives • Participate in all stages of software development, including front-end, back-end, database integrations, network and hosting management, user interface, user experience, and server management • Diagnose failure modes in learned or optimized policies • Build and operate large-scale production systems serving millions of users • Implement reinforcement learning, operations research methods, or simulation-driven decision systems in production • Develop large-scale ML and data pipelines • Track experiments, manage models, and manage artifacts with MLflow • Ship systems that operate reliably under production load • Work independently on moderately complex to complex technical decisions and influence department strategy • Attend occasional training, meetings, or conferences as required

🎯 Requirements

• 5+ years of post-undergraduate software engineering or quantitative research experience building and operating large-scale production systems • 2+ years of post-graduate software engineering or quantitative research experience building and operating large-scale production systems • 2+ years of hands-on experience implementing reinforcement learning, operations research methods, or simulation-driven decision systems in production • Experience with data-intensive platforms, recommendation systems, optimization engines, or simulation frameworks serving millions of users • Knowledge of policy-gradient and value-based reinforcement learning, including PPO, A3C, DQN, and CQL • Knowledge of stochastic dynamic programming, discrete-event simulation, or large-scale combinatorial or constrained optimization • Deep familiarity with Markov Decision Processes, Bellman-equation-based value estimation, reward/objective shaping, exploration-exploitation tradeoffs, and constraint formulation • Ability to diagnose policy failure modes, including instability, poor long-horizon credit assignment, and distributional shift • Proficiency in Python 3.x • Experience with PyTorch or TensorFlow • Experience with Ray RLlib or equivalent distributed computation frameworks • Experience with Databricks, PySpark, and Delta Lake for large-scale ML or data pipelines • Experience with MLflow for experiment tracking, model registry, and artifact management • Experience shipping reliable production-load systems, beyond research or prototype work • Preferred: experience with multi-agent RL frameworks such as PettingZoo • Preferred: familiarity with linear programming, mixed-integer programming, Lagrangian relaxation, or constraint programming • Preferred: experience in regulated domains such as healthcare, finance, or insurance • Preferred: experience with Gymnasium, SimPy, AnyLogic, or equivalent simulation frameworks • Preferred: familiarity with event-driven feedback loops and retraining or re-optimization pipelines • Preferred: OpenTelemetry instrumentation experience • Ability to provide a high-speed DSL or cable modem for a home office, with minimum 25 Mbps download and 10 Mbps upload • Satellite and wireless internet service is not allowed • Dedicated workspace without ongoing interruptions to protect member PHI/HIPAA information

🏖️ Benefits

• Bonus incentive plan based upon company and/or individual performance • Medical benefits • Dental benefits • Vision benefits • 401(k) retirement savings plan • Paid time off • Company holidays • Personal holidays • Paid parental leave • Paid caregiver leave • Short-term disability • Long-term disability • Life insurance • High-speed internet requirement/support; California home-based associates are provided payment for internet expense • Remote work arrangement • Occasional travel to Humana offices or Tech Hubs for training or meetings • Professional development/training opportunities