Principal Analyst, Operations and Health Systems Research

About This Role

Biogen studies highly complex, devastating, and burdensome diseases and there are still significant challenges in how we understand and treat them.

Biogen studies highly complex, devastating, and burdensome diseases and there are still significant challenges in how we understand and treat them.
In the Quantitative Sciences Development Organization we aspire to transform patients’ lives by accelerating disease research using best in breed and emerging techniques. Leveraging applied machine learning and emerging technologies, we drive solutions to advance research, clinical care, and patient empowerment.
We stand with our colleagues across Biogen developing pioneering treatments. We believe that now, more than ever, biology and technology should go hand-in-hand to better meet patient needs, while enabling a shift towards more prevention-focused, affordable, and equitable care.

As a Principal Analyst, Operations and Health Systems Research, you will:

• 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 in order to build epidemiological and disease forecasting models used to support decision-making for clinical trial operations
• Leverage methods from operations research such as constraints-based optimization, linear and non-linear programing, simulation and network modeling to understand participant, investigator, and sponsor behaviors that drive risk, benefit, and uncertainty in clinical trial outcomes.
• Generate evidence and communicate results, including at conferences and in peer-reviewed publications for audiences in the therapeutic area of 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.

You are passionate about exploring and establishing new methods for looking at data across devices, applications, data streams, and diseases. You love figuring out how to create mathematical and statistical models that relate human biology, clinical development, and sensor technology to business outcomes and patient needs.

• >= 5 years Pharma/Biotech/Tech/Healthcare industry experience, alternatively extensive experience in academic/clinical centers of excellence
• Expertise in leveraging electronic health records and other data sources derived from clinical care via state-of-the-art methodologies, programming languages, and tools
• Experience working on machine learning operations research, and data science problems using formal software development lifecycle approaches and best practices as part of a software delivery organization
• Profound experience in data science, machine learning, operations research and data engineering programming using python/R and higher-level libraries such as numpy, pandas, scipy, stats models, scikit-learn, Google OR Tools, Tensor Flow/PyTorch, pyspark, tidyverse, sparklyr, mlr, tidy models or similar
• Strong familiarity with simulation and forecasting models used by business stakeholders and experience in communicating results and improving models given feedback from end-users

• Experienced in communicating and building consensus on highly technical or sensitive information with technology and business teams
• Experience iterating through UI/UX patterns, data visualization, and front-end interactions and balancing across conflicting stakeholder preferences
• Formal application of principles of empirical science including statistical modeling, design of experiments, and hypothesis formulation and testing
• Advanced degree in public health, epidemiology, public health economics, operations research or a similar discipline

Job Level: Management

The base compensation range for this role is: $-$

Base salary offered is determined through an analytical approach utilizing a combination of factors including, but not limited to, relevant skills & experience, job location, and…