Senior Manager, Predictive Analytics

We are seeking a highly motivated and talented Senior Manager of Predictive Analytics to join the Regeneron Genetics Center (RGC) to pioneer clinical use cases for proteomic and genomic data. In this role, you will develop and apply predictive models on the world's largest integrated datasets of genomics, proteomics, and electronic medical records.

The role involves partnering with cross-functional teams, including Business Development, Laboratory staff, and other scientific groups, to foster collaboration and advance key initiatives. The candidate must have the ability to influence, with strong interpersonal skills.

Key Responsibilities

• Plan, develop, and execute large-scale analyses of proteomic and genomic datasets, with an emphasis on aging and age-related diseases
• Develop and implement methods for data harmonization and normalization across distinct cohorts to ensure consistency and reproducibility of results
• Evaluate statistical methods for disease risk prediction, and if necessary develop new methods
• Turn disease prediction needs from other teams and collaborators into concrete project/budget proposals
• Stay informed on emerging market trends in disease prediction and applications of genomics data to continuously refine research directions
• Deliver clear and concise presentations of genomics and proteomic findings to leadership, ensuring alignment with organizational goals and priorities
• Ability to provide data to internal, external, and non-scientific audience
• Design, implement, and optimize data pipelines for high-throughput genomic and proteomic workflows
• Develop and integrate robust quality control (QC) measures at multiple stages of analysis pipelines

Preferred Qualifications

• Demonstrated expertise in statistics, machine learning and predictive analytics applied to biological data
• Demonstrated aptitude for translating research results into products or prototypes
• Proven ability to independently lead and manage research projects from conception to completion
• Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams
• Demonstrated ability to present data, insights, and recommendations effectively to stakeholders at all levels

Requirements

• PhD in a relevant field (e.g., human genetics, statistics, computational biology, or related disciplines) and at least 5 years of experience analyzing large-scale genomics data, or a bachelor's degree with at least 8 years of relevant experience
• Candidates with prior industry experience are preferred
• Experience in exploratory data analysis, applied statistics, or software engineering preferred