Senior Decision Intelligence Engineer – NBA

🔥 vor 12 Stunden

🇺🇸 Vereinigte Staaten – Remote

💵 $106.900 - $147.000 / Jahr

⏰ Vollzeit

🟠 Senior

👷🏻‍♀️ Ingenieur

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

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Humana

WebsiteLinkedInAlle Stellen

10.000+ Mitarbeiter

Gegründet 1961

🏥 Gesundheitswesen

🛡️ Versicherung

⚕️ Krankenversicherung

Healthcare • Insurance • Healthcare Insurance

Humana ist ein Gesundheitsunternehmen, das sich zum Ziel gesetzt hat, die Gesundheit von Individuen, Gemeinschaften und dem Gesundheitssystem insgesamt positiv zu beeinflussen. Mit einem klaren Fokus darauf, Gesundheit an erste Stelle zu setzen, bedient Humana eine vielfältige Zielgruppe, darunter Senioren und das Militär, und bietet Medicare Advantage HMO-, PPO- und PFFS-Pläne an. Humana engagiert sich für eine Kultur der Zugehörigkeit und des gegenseitigen Respekts und bietet wettbewerbsfähige und flexible Vorteile, um die finanzielle Sicherheit seiner Mitarbeiter und deren Familien zu gewährleisten. Das Unternehmen ist stolz darauf, einen inklusiven Arbeitsplatz zu schaffen, an dem jeder die Möglichkeit hat, erfolgreich zu sein.

Beschreibung

• 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

🎯 Anforderungen

• 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

🏖️ Vorteile

• 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