Senior Manager, Predictive Analytics

Role Summary

Senior Manager of Predictive Analytics to join the Regeneron Genetics Center (RGC) to pioneer clinical use cases for proteomic and genomic data. Develop and apply predictive models on large integrated datasets of genomics, proteomics, and electronic medical records. Partner with cross-functional teams to foster collaboration and advance key initiatives; the role requires the ability to influence and strong interpersonal and communication skills for a collaborative environment.

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 audiences.
• Design, implement, and optimize data pipelines for high-throughput genomic and proteomic workflows, ensuring efficient processing of large-scale proteomic datasets.
• Develop and integrate robust quality control (QC) measures at multiple stages of analysis pipelines to ensure data accuracy, consistency, and reproducibility.

Qualifications

• Preferred: Demonstrated expertise in statistics, machine learning and predictive analytics applied to biological data.
• Preferred: Demonstrated aptitude for translating research results into products or prototypes.
• Preferred: Proven ability to independently lead and manage research projects from conception to completion.
• Preferred: Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams.
• Preferred: Demonstrated ability to present data, insights, and recommendations effectively to stakeholders at all levels of the organization.
• Required: A PhD in a relevant field (e.g., human genetics, statistics, computational biology, or related disciplines) and at least five years of experience analyzing large-scale genomics data, or a bachelor's degree with at least 8 years of relevant experience.
• Preferred: Candidates with prior industry experience are preferred.
• Preferred: Experience in exploratory data analysis, applied statistics, or software engineering is preferred in one or more of these domains.