Health Data Researcher, Data & Insights

at  Walgreens

JOB SUMMARY

This role will develop and deploy generative artificial intelligence and machine learning (GenAI/ML) models 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.
As a member of the Walgreens Data & Insights group, this highly visible role will influence next generation solution design and roadmap decisions as part of Walgreens generative AI/machine learning 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 generative AI/machine learning advisory workshops as a data science subject matter expert.

Job Responsibilities

• 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, managed data in Azure Data Lake Storage / Snowflake.
• Model Building: Serve data to feature store, create training sets, push training data to Spark dataframes, 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 DataBricks 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

BASIC QUALIFICATIONS

• 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 and deploying logically-separated data environments using machine learning services that include but are not limited to Azure Data Factory, Microsoft Fabric, Databricks, or Snowflake.
• Excellent organizational, planning, and project management skills with strong attention to detail and ability to effectively manage cross-functional projects.
• Experience establishing and maintaining key relationships with internal (peers, business partners and leadership) and external (business community, clients and vendors) within a matrix organization to ensure quality standards of service are met and collaborative problem solving is practiced.
• Strong oral and written communication skills.
• Willing to travel up to/at least 10% of the time for business purposes (within state and out of state).

PREFERRED QUALIFICATIONS

• Graduate degree in Data Science, Computer Science, Informatics, or other quantitative field or related work experience.
• Familiarity applying Responsible AI fairness practices and evaluation systems to train generative AI models using unbiased data sets.
• Working knowledge of standard healthcare data sources, e.g., Symphony patient claims data and sub-national data, IQVIA National Prescription data, CMS Medicare CCLF claims files, and Medicare Part D drug claims files.

• 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, managed data in Azure Data Lake Storage / Snowflake.
• Model Building: Serve data to feature store, create training sets, push training data to Spark dataframes, 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 DataBricks 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 customer