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The Senior Decision Intelligence Engineer is a hands-on individual contributor responsible for building, deploying, and operating ML and decisioning pipelines for the NBA Decision Intelligence Platform.

This role focuses on production pipeline development, MLOps, feature engineering, scoring workflows, monitoring, and optimization-aware decisioning. You will help ensure the platform selects the right action for the right member while respecting clinical eligibility, suppression rules, channel constraints, program goals, and operational capacity.

You will work closely with ML engineers, data engineers, platform engineers, product owners, and decision engine teams to deliver reliable, scalable, and auditable production systems.

ML Pipeline and MLOps Development

• Build and maintain production pipelines for feature generation, model training, evaluation, scoring, deployment, and monitoring.

• Develop reusable pipeline components using Python, PySpark, Databricks, Delta Lake, and MLflow.

• Support CI/CD, automated validation, model versioning, artifact management, rollback, and release workflows.

• Monitor model performance, data quality, drift, scoring outcomes, and operational health.

• Troubleshoot production issues across feature pipelines, scoring jobs, model artifacts, and downstream integrations.

Feature Engineering and Scoring

• Build and maintain member feature pipelines using clinical, behavioral, engagement, operational, web clickstream, and socioeconomic data.

• Ensure features are reproducible, auditable, governed, and performant within the Databricks Lakehouse.

• Operate batch and near-real-time scoring workflows that support personalized outreach across email, SMS, direct mail, digital, and care team channels.

• Integrate model outputs into decisioning platforms, campaign systems, and operational workflows.

Decisioning and Optimization

• Contribute to optimization logic for next-best-action selection, constrained ranking, member prioritization, and resource allocation.

• Translate business and clinical rules into structured constraints, scoring adjustments, objective functions, and prioritization logic.

• Help balance member relevance, program objectives, outreach limits, channel availability, eligibility rules, suppression periods, and operational capacity.

• Monitor decisioning behavior for scoring anomalies, constraint violations, data issues, and SLA risks.

Experimentation, Safety, and Governance

• Support A/B testing, holdout testing, and measurement workflows for evaluating model and decisioning effectiveness.

• Build automated evaluation gates to prevent underperforming models or scoring workflows from being promoted.

• Validate output quality, action distributions, rule alignment, and downstream decision behavior before production release.

• Document pipeline behavior, assumptions, known limitations, and operational runbooks.

• Support compliance, auditability, explainability, and privacy expectations in a regulated healthcare environment.

Collaboration and Engineering Practices

• Partner with ML engineering, data engineering, platform, product, rules engine, and decision engine teams.

• Participate in design reviews, code reviews, operational readiness reviews, and production support.

• Communicate implementation tradeoffs, production risks, optimization assumptions, and delivery status clearly.

• Use AI-assisted engineering tools such as GitHub Copilot, Claude, or similar platforms to improve development speed and quality.

Use your skills to make an impact
 

Requirements

• 5+ years of experience in machine learning engineering, MLOps, data engineering, platform engineering, optimization engineering, or related software engineering roles.

• Strong hands-on experience with Python, PySpark, SQL, and distributed data processing.

• Experience building and operating production ML pipelines using Databricks, MLflow, Airflow, or equivalent platforms.

• Experience with CI/CD, testing, observability, deployment automation, model monitoring, and production support.

• Experience with cloud-based data platforms such as Databricks, Snowflake, AWS, Azure, or GCP.

• Familiarity with model lifecycle management, experiment tracking, artifact versioning, and release workflows.

• Working knowledge of optimization concepts such as constrained ranking, objective functions, threshold tuning, prioritization, or capacity constraints.

• Ability to translate business rules and operational constraints into reliable production logic.

• Strong troubleshooting skills and ability to operate effectively in complex production environments.

• Clear communication skills and ability to collaborate across technical and non-technical teams.

Preferred

• Experience with personalization, recommendation systems, next-best-action platforms, or decisioning engines.

• Experience with constrained optimization, linear programming, mixed-integer programming, heuristic optimization, or simulation-based evaluation.

• Familiarity with optimization tools such as OR-Tools, SciPy Optimize, PuLP, Pyomo, Gurobi, or equivalent.

• Knowledge of Databricks Lakehouse, Unity Catalog, Delta Lake, Jobs Workflows, and MLflow.

• Experience with Kafka, event-driven pipelines, streaming data, or feedback-loop design.

• Experience in healthcare, insurance, or other regulated environments involving PHI, HIPAA, auditability, and explainability.

• Experience with feature stores, real-time inference, OpenTelemetry, Terraform, or production observability tooling.

Work at Home Requirements: To ensure Home or Hybrid Home/Office employees’ ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.

 

Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required.

 

Scheduled Weekly Hours

40

Pay Range

The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.

 

$106,900 - $147,000 per year

 

This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.

Description of Benefits

Humana, Inc. and its affiliated subsidiaries (collectively, “Humana”) offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides 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 and many other opportunities.

About us
 

About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com.

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Equal Opportunity Employer

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.