Humana

Data Scientist

• Manage data to support and influence decisions on day-to-day operations, strategic planning and specific business performance issues
• Lead the revenue and risk score forecasting of Humana’s End Stage Renal Disease (ESRD) population across bids, budget, and forecast cycles
• Drive monthly current‑year forecasting, analyze membership and ESRD cohort mix changes, assess CMS model and policy impacts, and deliver early insights to leadership
• Work closely with team members to solve complex problems through collaboration and supports business partners across the enterprise including Actuarial, Finance, and Operations

Risk Adjustment Financial Analytics Lead

Medical Director

• Responsible for behavioral health care strategies and/or operations
• Make determinations whether requested services, requested level of care, or requested site of service should be authorized
• Work includes computer-based review of moderately complex to complex clinical scenarios
• Conduct discussions with external physicians by phone to gather additional clinical information or discuss determinations
• Support regional market priorities
• Report directly to the Lead Behavioral Health Medical Director

Medical Director – BH/MH

Sales

• Responsible for leading overall Partner channel sales strategy and transformation to drive membership growth, member retention, and cost per sale.
• Build and expand relationships with external partners to promote, accelerate and drive Senior Product sales across all field channels, responding to unforeseen market changes and consumer buying preferences.
• Scale intelligent enablement (e.g., call effectiveness tools, CRM adoption, playbooks) to improve contact, conversion, and throughput.
• Set quarterly objectives and KPIs for all partner types (Field, CC/BPO, FMOs) and hold leaders accountable with transparent dashboards.
• Champion an enterprise growth mindset that prioritizes STARs, member outcomes, and complaint reduction (CTM/k).
• Implement progressive oversight policies to proactively address outliers (e.g., accretion, CTMs) and ensure end-to-end CMS compliance in partner operations, sales practices, and marketing activations.
• Lead a high-performing leadership bench (5 direct reports; ~200 associates) with clear roles, operating rhythms, and success metrics skilled at data-driven decision-making, change leadership, and cross-functional collaboration.
• Build and sustain a best-in-class partner operating cadence (planning, enablement, execution, inspection, and continuous improvement).

VP, Partner Sales Channel

Engineer

• Design, implement, and evaluate RL algorithms suited to long-horizon, sparse-reward healthcare decisioning, including policy gradient methods (PPO, A3C), value-based approaches (DQN, Q-learning), and offline RL methods (CQL, Decision Transformer).
• Define and maintain the member state representation and action space, evolving both as new programs and data sources are onboarded.
• Apply the Bellman equation, reward shaping, and constraint mapping to encode clinical eligibility, suppression rules, and program-specific objectives directly into the learning objective.
• Manage exploration-exploitation tradeoffs appropriate for a production healthcare environment where poorly explored actions have real member impact.
• Build simulation and backtesting environments to evaluate policy quality before production promotion, using historical member journey data.
• Diagnose and remediate common RL failure modes: policy collapse, credit assignment errors across long member journeys, and distributional shift between training and serving populations.
• Own the nightly Databricks training workflow: feature engineering from Gold Activity History and Gold Patient Profile, state vector normalization, distributed RL training via Ray RLlib, and batch scoring of all 8M eligible members.
• Collaborate with the Data Engineering team (Decisioning Team 2) to ensure training inputs are correctly joined, reward signals are accurately computed from disposition outcomes, and the feature pipeline is reproducible and auditable.
• Write production-quality PySpark feature engineering jobs; maintain data lineage through Databricks Unity Catalog.
• Manage model artifacts, versioning, and lifecycle in the MLflow Model Registry; ensure rollback capability is maintained at all times.
• Apply multi-agent RL concepts (MARL via PettingZoo) where member household or population-level coordination is required.
• Implement constraint mapping to enforce hard business rules — member caps, cooldown periods, clinical eligibility — as constraints within the RL objective rather than downstream filters.
• Collaborate with the Rules Engine team to ensure Drools eligibility guards and RL policy priorities are correctly aligned and do not conflict.
• Partner with Decisioning Team 1 (Decision Engine, Rules Engine) to ensure model outputs integrate cleanly with the real-time decisioning hot path and that scored recommendations cached in Redis are correctly structured and interpreted.
• Document model behavior, known limitations, and failure modes for clinical and compliance stakeholders; support explainability requirements for member-facing decisions.

Decision Intelligence Engineer – Next Best Action

Business Analyst

• Performs analysis of business, process and user needs
• Documentation of requirements
• Cost/benefit analysis and translation into proper system requirement specifications
• Validates benefits achieved from solution implementation
• Influences department's strategy
• Works independently with moderately complex to complex issues
• Collaborates with Tech on report delivery for Finance customers

Senior Business Analyst

Manager

• Develops business processes to ensure successful submission and reconciliation of encounter submissions to Medicaid/Medicare
• Ensures encounter submissions meet or exceed all compliance standards via analysis of data
• Develops tools to enhance the encounter acceptance rate by Medicaid/Medicare
• Looks for long-term improvements of encounter submission processes
• Makes decisions on resources, approach, and operations of day-to-day focus
• Leads a team of associates who develop efficient business processes for Error Corrections
• Ensures successful submission and reconciliation of encounter submissions across multiple Medicare/Medicaid trading partners
• Plays a key role in influencing departmental strategy

Manager, Encounter Data Management

Product Manager

• Own the full MA shopping, decision, and renewal journey—from awareness to plan selection—leveraging data, insights, and research to guide continuous iteration.
• Identify friction points, conversion barriers, and opportunities to enhance clarity and confidence for prospects and members.
• Partner cross‑functionally with Product, Marketing, Operations, and Support to deliver journey improvements and aligned messaging.
• Define and maintain journey-level KPIs; guide the development of dashboards to monitor funnel performance and customer behavior changes.
• Facilitate cross-functional workshops to communicate journey insights, align on strategy, and prioritize experience investments.
• Champion scalable component design to ensure consistency across storefront pages, plan display modules, and conversion flows.

Lead Product Manager, Digital Shopping Journey

Administration

• provides non-clinical support for policies ensuring the most appropriate treatment, care or services for members
• manage NLP's for chart reviews for the nursing team
• build and pend authorizations for review
• perform inbound and outbound calls to engage providers and members to verify clinical information/discharge date and admission status
• document completed calls and attach clinical information received
• request clinical information from providers/facilities
• create written correspondence
• create and distribute determination letters
• collaborate with multiple roles/departments/providers/team members

Utilization Management Coordinator – SNF

Data Engineer

• Use data architecture, data integration, and interoperability best practices to make data available for analytics teams.
• Work with CenterWell data and Humana membership data.
• Optimize data loading, storing, modeling, and pipelining.
• Develop blueprints for all data repositories.
• Translate needs into long-term data architecture solutions.
• Design and build dimensional database schemas.
• Evaluate reusability of current data for separate analyses.
• Conduct data sheering to rid the system of old, unused or duplicate data.
• Review object and data models and the metadata repository.

Senior Data Architect

Director

• initiates, negotiates, and executes physician, hospital, and/or other provider contracts and agreements
• communicates contract terms, payment structures, and reimbursement rates to providers
• analyzes financial impact of contracts and terms
• maintains contracts and documentation within a tracking system
• assists with identifying and recruiting providers based on network composition and needs
• implements strategic plans, drives goals and objectives, and improves performance.
• provides input into functions strategy

Director, Provider Contracting

• Serve as a technical expert for Snowflake and Azure , leading hands ‑ on implementation across ingestion, transformation, orchestration, and platform optimization.
• Develop and maintain API ‑ driven integrations using MuleSoft , enabling secure, scalable connectivity between cloud and on ‑ prem systems.
• Drive the migration from on ‑ prem SQL Server environments to Snowflake , including re ‑ architecting pipelines, data models, and workflows for the cloud.
• Implement engineering best practices, including CI/CD for data, infrastructure ‑ as ‑ code, version control, testing frameworks, and observability.
• Independently troubleshoot complex data and platform issues , identifying root causes and designing effective long ‑ term solutions.
• Collaborate with data architects, analysts, and business partners to translate requirements into robust, production ‑ ready solutions.
• Mentor and support data engineers , providing technical guidance, code reviews, and thought leadership to elevate engineering standards.
• Optimize data models, storage patterns, and compute usage to ensure cost ‑ efficient and high ‑ performance operations.
• Partner with IT, security, and governance teams to ensure compliance, data quality, and secure handling of sensitive healthcare data.
• Evaluate and introduce new tools, frameworks, and cloud capabilities that enhance our data platform and engineering productivity.

Lead Data Engineer

Financial Planning and Analysis

• Analyzes and forecasts financial, economic, and other data to provide accurate and timely information for strategic and operational decisions
• Collects, compiles, verifies, and analyzes financial data and economic indicators
• Evaluates industry, financial, and market trends to forecast organization’s financial and competitive position
• Supports financial decisions through comprehensive data extraction, analysis, and reporting
• Utilize expertise in data mining to manage complex datasets and generate actionable insights
• Responsibilities may include financial modeling, reporting, and budgeting

Financial Planning and Analysis Professional

Security Engineer

• Serve as the primary strategic owner for assigned supplier relationships
• Lead and mature supplier governance including quarterly business reviews (QBRs), executive business reviews, steering committees, and strategic roadmaps
• Oversee contract strategy, including renewals, enterprise licensing, SaaS agreements, consumption models, pricing optimization, and SLA development
• Partner closely with IT, Security, Finance, Legal, Architecture, and business leaders to drive alignment between business requirements and vendor capabilities
• Lead escalations, risk mitigation, service remediation, and performance correction plans to ensure vendor accountability
• Manage enterprise financials for assigned suppliers including cost optimization, forecasting, ROI, and long-term investment planning
• Maintain deep awareness of market trends, supplier risk, and competitive landscapes within portfolio
• Influence executive stakeholders using strong communication, storytelling, and analytical reasoning
• Contribute to vendor management maturation including frameworks, dashboards, and governance tools

IT Vendor Management Lead – Cybersecurity, Identity Platforms, Resellers

Insurance

• Independently managing and delivering high-profile, high-impact strategy projects end-to-end, from developing an approach to delivering recommendations and final deliverables
• Leading high quality, high impact deliverables for Humana’s Board of Directors and Executive Leadership Team, including multi-year line of business strategies, the business unit’s annual strategic plan, and executive strategy presentations
• Leading critical processes to prepare leadership for interactions with Humana’s Executive Leadership Team and Board of Directors
• Overseeing and delivering high quality analysis and deliverables that clearly frame objectives, issues/challenges, and articulate compelling, insightful findings, conclusions, and recommendations
• Overseeing development of hypothesis to be validated or refined through targeted research and analysis
• Conducting interviews, working sessions, and report-outs with leaders across the company
• Overseeing industry, market, competitor, and financial analysis
• Working collaboratively with fellow team members and leaders across the company
• Effectively leading and developing junior members of the team, including multiple direct reports
• Being a steward of the company and strategy team’s operating model, norms and ways of working

Director, Insurance Business Unit Strategy

• AI solutions using Python, computer vision, and generative models like LLMs and diffusion models.
• Build autonomous AI agents using frameworks (i.e. LangChain, LangGraph, AutoGen, CrewAI).
• Embed AI into Humana’s systems and workflows.
• Partner with business teams to understand challenges, co-create solutions, and communicate AI capabilities clearly.
• Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production.
• Manage the execution of data science strategies and initiatives.
• Guide and execute the strategic decision in collaboration with data scientists, software engineers, and stakeholders.
• Lead the development and maintenance of complex machine learning models and algorithms.
• Design and implement robust monitoring capabilities to maintain optimal performance and reliability.