Principal Analyst, Operations and Health Systems Research
Biogen
August 18, 2026
Remote friendly (Cambridge, MA)
United States
Operations
What You’ll Do:
- Design, develop, and implement complex end-to-end data pipelines; engineer features and forecasting models to understand the intersection of health systems utilization and clinical research.
- Integrate real-world data sources to build epidemiological and disease forecasting models that support decision-making for clinical trial operations.
- Use operations research methods (constraints-based optimization, linear/non-linear programming, simulation, network modeling) to understand participant, investigator, and sponsor behaviors driving risk, benefit, and uncertainty in clinical trial outcomes.
- Generate evidence and communicate results (conferences and peer-reviewed publications) for therapeutic area interest, sensor science, machine learning, and operations research.
- Support integration, design, and development of novel measures, models, and metrics to assess model validity and performance across the model lifecycle.
Who You Are:
- Passionate about developing new methods for analyzing data across devices, applications, data streams, and diseases; enjoy creating mathematical/statistical models linking human biology, clinical development, and sensor technology to business outcomes and patient needs.
Required Skills:
- 5+ years pharma/biotech/tech/healthcare experience (or extensive academic/clinical centers of excellence experience).
- Expertise leveraging electronic health records and other clinical-care-derived data sources.
- Experience in machine learning operations research and data science using formal software development lifecycle approaches.
- Proficiency with data science/ML/OR/data engineering in Python/R and libraries including numpy, pandas, scipy, statsmodels, scikit-learn, Google OR Tools, TensorFlow/PyTorch, pyspark, tidyverse, sparklyr, mlr, tidymodels (or similar).
- Familiarity with simulation and forecasting models; ability to communicate results and improve models based on end-user feedback.
Preferred Skills:
- Communicate complex/sensitive information and build consensus with technology and business teams.
- Experience with UI/UX patterns, data visualization, and front-end interactions.
- Formal empirical science (statistical modeling, design of experiments, hypothesis testing).
- Advanced degree in public health, epidemiology, public health economics, operations research, or similar.
Benefits:
- Medical, dental, vision, and life insurance; fitness/wellness reimbursement; short- and long-term disability insurance; 15+ days paid vacation and end-of-year shutdown (Dec 26–Dec 31); paid holidays and personal days; sick time; paid maternity and parental leave; 401(k) with company match; employee stock purchase plan; tuition reimbursement (up to $10,000/year); employee resource groups participation.
- Design, develop, and implement complex end-to-end data pipelines; engineer features and forecasting models to understand the intersection of health systems utilization and clinical research.
- Integrate real-world data sources to build epidemiological and disease forecasting models that support decision-making for clinical trial operations.
- Use operations research methods (constraints-based optimization, linear/non-linear programming, simulation, network modeling) to understand participant, investigator, and sponsor behaviors driving risk, benefit, and uncertainty in clinical trial outcomes.
- Generate evidence and communicate results (conferences and peer-reviewed publications) for therapeutic area interest, sensor science, machine learning, and operations research.
- Support integration, design, and development of novel measures, models, and metrics to assess model validity and performance across the model lifecycle.
Who You Are:
- Passionate about developing new methods for analyzing data across devices, applications, data streams, and diseases; enjoy creating mathematical/statistical models linking human biology, clinical development, and sensor technology to business outcomes and patient needs.
Required Skills:
- 5+ years pharma/biotech/tech/healthcare experience (or extensive academic/clinical centers of excellence experience).
- Expertise leveraging electronic health records and other clinical-care-derived data sources.
- Experience in machine learning operations research and data science using formal software development lifecycle approaches.
- Proficiency with data science/ML/OR/data engineering in Python/R and libraries including numpy, pandas, scipy, statsmodels, scikit-learn, Google OR Tools, TensorFlow/PyTorch, pyspark, tidyverse, sparklyr, mlr, tidymodels (or similar).
- Familiarity with simulation and forecasting models; ability to communicate results and improve models based on end-user feedback.
Preferred Skills:
- Communicate complex/sensitive information and build consensus with technology and business teams.
- Experience with UI/UX patterns, data visualization, and front-end interactions.
- Formal empirical science (statistical modeling, design of experiments, hypothesis testing).
- Advanced degree in public health, epidemiology, public health economics, operations research, or similar.
Benefits:
- Medical, dental, vision, and life insurance; fitness/wellness reimbursement; short- and long-term disability insurance; 15+ days paid vacation and end-of-year shutdown (Dec 26–Dec 31); paid holidays and personal days; sick time; paid maternity and parental leave; 401(k) with company match; employee stock purchase plan; tuition reimbursement (up to $10,000/year); employee resource groups participation.