Key skills
AirflowCloudKubernetesPythonPyTorchScikit-LearnSQLTableauTensorflowRMachine LearningMLTensorFlowscikit-learnMLOpsXGBoostData EngineeringAnalyticsBIBusiness IntelligencePower BIdbtStatistical AnalysisProduct ManagementA/B TestingAccount Management
About this role
Role Overview
- Lead the development and delivery of advanced analytics solutions to support market access and pricing decisions
- Perform sophisticated analyses on patient longitudinal data, develop interactive dashboards and reports
- Translate complex data into actionable insights for stakeholders
- Design, develop, and deploy predictive models and analytical solutions using Dagster/Airflow and DBT workflows
- Architect and maintain scalable datasets that integrate with existing data engineering infrastructure
- Create interactive dashboards and reports using business intelligence tools
- Perform advanced statistical analysis on patient longitudinal data and large customer datasets
- Develop and implement machine learning algorithms to enhance forecasting capabilities
- Collaborate closely with the data engineering team, SQL developers, and analytics product management
- Serve as the technical bridge between data engineering infrastructure and business-facing analytics
- Partner cross-functionally with Pricing, Contract Development, Value and Access, Account Management, Finance, Forecasting, and Data Management teams
- Communicate complex analytical findings through compelling data narratives and visualizations
- Continuously evaluate and implement emerging methodologies and technologies in data science
Requirements
- 5+ years of experience in data science or advanced analytics within Pharmaceutical or Payer organizations
- 5+ years of hands-on experience building and deploying predictive models and machine learning solutions on large-scale datasets
- Demonstrated experience working with workflow orchestration tools (Dagster, Airflow, or similar) to productionize analytical models
- Proven track record of translating business problems into data science solutions that drive measurable outcomes
- Experience collaborating with data engineering teams and contributing to data pipeline development
- Advanced proficiency in Python or R for statistical modeling, machine learning, and data analysis
- Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) and predictive modeling techniques
- Hands-on experience with workflow orchestration platforms (Dagster, Airflow, Prefect, or similar)
- Proficiency in SQL for complex data manipulation and working with relational databases
- Expertise in data visualization tools (Tableau, Power BI, or similar) and creating executive-level dashboards
- Experience with cloud platforms (Kubernetes) and modern data stack technologies
- Strong foundation in statistical methods, experimental design, and A/B testing
- Understanding of MLOps principles and model deployment best practices
- Deep understanding of pharmaceutical market access, pricing strategies, and reimbursement dynamics
- Experience analyzing longitudinal patient data, claims data, and formulary datasets
- Working knowledge of the US healthcare system, payer landscape, and regulatory environment
- Familiarity with healthcare data standards (e.g., NDC, HCPCS, ICD codes, IQVIA)
Tech Stack
- Airflow
- Cloud
- Kubernetes
- Python
- PyTorch
- Scikit-Learn
- SQL
- Tableau
- Tensorflow
Benefits
- health insurance
- prevention and wellness programs
- at least 14 weeks’ gender-neutral parental leave