Machine Learning Engineer, Omics and Patient Data Integration

$107,000 - $171,000/Yr

Biogen - Cambridge, MA

Full-time - Mid Level

Cambridge, MA

1,001-5,000 employees

Chemical Manufacturing

About the position

As a Machine Learning Engineer specializing in Omics & Patient Data Integration at Biogen, you will play a crucial role in integrating complex omics data with real-world data sources to develop advanced statistical and machine learning models. Your work will support decision-making in clinical trials and contribute to the development of pioneering treatments that transform patients' lives. You will collaborate with cross-functional teams to ensure data quality and integrity while communicating findings through reports and visualizations.

Responsibilities

• Integrate omics data with real-world data sources to develop and implement advanced statistical and machine learning models.
• Support integration, design, and development of novel measures, models, and metrics to assess model validity and performance.
• Communicate findings and insights through clear and concise reports, presentations, and visualizations.
• Collaborate closely with cross-functional teams, including clinical researchers, biostatisticians, and IT specialists.

Requirements

• 5+ years of experience in Pharma/Biotech/Tech/Healthcare industry or extensive experience in academic/clinical centers of excellence.
• Proven experience in developing and deploying machine learning models and statistical analysis, preferably in the context of omics data and healthcare applications.
• Expertise in leveraging omics data along with electronic health records and other data sources derived from clinical care.
• Experience in managing complex, interdisciplinary research and development projects, especially in software and technology implementation.
• Profound experience in data science, machine learning, and data engineering programming using R and Python.

Nice-to-haves

• Experience in communicating and building consensus on difficult or sensitive information with technology and business teams.
• Familiarity with formal software development lifecycle approaches and best practices in machine learning and data science problems.
• Advanced degree in quantitative science such as statistics, applied mathematics, or computational biology.

Benefits

• Medical insurance
• Dental insurance
• Life insurance
• Long and short-term disability insurance
• Vacation
• End-of-year shutdown
• 401K participation and matching contributions