Senior Health Data Engineer

This role will develop and deploy scalable data pipelines, data models and analytical solutions from Walgreens real-world data (RWD) warehouses using a full suite of data science platform technologies. As a data scientist, this role will collaborate closely with data, technology, and business teams to develop intelligent solutions for healthcare and life science clients.

This highly visible role will influence next generation solution design and roadmap decisions as part of Walgreens data productization and commercialization strategy. Role will serve as a critical member of client delivery teams that will actively lead technical sessions as part of solution pilots and participate in requirement and design sessions as a healthcare data subject matter expert.

• Lead generative AI and machine learning project teams through the model development lifecycle across data pre-processing, model building, model evaluation, and model serving stages.
• Data Pre-Processing:
  Configure data connections/APIs, tokenize text strings, manage data in Azure Data Lake Storage / Snowflake.
• Model Building:
  Serve data to feature store, create training sets, push training data to Spark data frames, write utilities to save performance metrics resulting from model training loops;
• Model Evaluation:
  Select and visualize model performance metrics (Precision vs. Recall, AUC), post-deployment model drift, and model output against ground truth baselines;
• Model Serving:
  Create Predict endpoints, run/deploy models to TorchScript, oversee REST endpoint model deployment, configure tracking servers.
• Collaborate with Walgreens business leads and client points-of-contacts to perform opportunity discovery (e.g., product-solution fit evaluations) to close client strategic analytics gaps with Walgreens Data & Insights advanced analytics solutions. Coordinate client-specific data requirements, PHI/PII handling protocols, and data exchange action plans to support solution development blueprints.
• Partner with Walgreens technical teams to architect, maintain, and scale a fully-functioning data science workbench across Snowflake and Data Bricks platforms that enables common model training, performance evaluation, and deployment tasks.
• Help define the Walgreens Data & Insights generative AI / machine learning use case portfolio and track delivery progress from inception through to deployment. Prioritize release of new solutions to initiate pilot programs with Pharma and Health Payer client teams.
• Maintain a high level of proficiency in the latest AI algorithms, libraries, and related technologies. Serve as a subject matter expert in vendor selection and evaluation as use cases call for additions to the Walgreens Data Science infrastructure and tool set.
• Develop project materials that effectively translate technical concepts and outcomes for business audiences to facilitate swift decision making. (e.g, presentations, white papers, industry webinars)
• Personify Walgreens 4C’s culture when collaborating with internal teams, stakeholders, and customers.

• Bachelor's degree and at least 4 years of experience in quantitative or computational functions; or graduate degree in a quantitative, computational or technical discipline.
• Experience working with healthcare and/or pharmacy data sets in Health Information Trust Alliance (HITRUST) certified environments (e.g., encryption tools, dynamic masking policies, tokenization).
• Working knowledge of common machine learning language and libraries such as SQL, Python, PySpark, DASK, PyTorch, Tensorflow, Keras in a production coding environment.
• Demonstrable project experience in the areas of machine learning, ensemble methods, data mining, and time series forecasting. Configuring…