Principal Product Manager - Data Scientist Platform

December 10

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Exact Sciences

WebsiteLinkedInAll Job Openings

Precision oncology • Genomic testing • Cancer screening • Genetic testing • Research and development

5001 - 10000 employees

Founded 1995

⚕️ Healthcare Insurance

🧬 Biotechnology

🔬 Science

Description

• The Principal Product Manager, Scientific Data Platform is responsible for the delivery of data products that power scientific analytics and AI initiatives across the enterprise through the Scientific Data Platform (SDP) • Collaborates with internal customers across the Science Office, Business Units, Exact Sciences Laboratories and other internal customers to understand their data needs for current and upcoming analytics and AI projects that require genetic, genomic, biologic, pathologic and clinical data • Maintains the SDP roadmap, and is responsible for translating the roadmap into prioritized features and data sets to be delivered on SDP • Ensures delivery of datasets and features in partnership with data engineering teams in Bioinformatics, Biostatistics, Data Management and Software (BBDS) and/or IT • Demonstrate and maintain technical leadership in organizing internal data (data FAIRification, data privacy, data governance) • Links internal data with external, real-world data sources (tokenization, identified data retrieval) • Uses AI technologies for data enrichment (extracting structured features from semi-structured and unstructured source data)

Requirements

• MS/PhD in Informatics, Computer Sciences, or a field related to the essential duties of the job • 8+ years of experience in Data Science, growing responsibility and complexity of role and deliverables over time • 5+ years of experience in Data Science specific to scientific health data (genomic, genetic, clinical, imaging data) • 2+ years of experience working in Agile teams • Demonstrated extensive experience with Databricks platforms • Demonstrated experience with AWS cloud platforms • Demonstrated experience in Data Architecture Design • Demonstrated experience with Machine Learning and predictive analytics • Demonstrated experience using statistical computer languages (R, Python, SLQ, etc.) • Demonstrated experience with building ETL and data processing pipelines • Demonstrated experience with one or more real-world data linking technology (tokenization, identified data linking)

Benefits

• paid time off (including days for vacation, holidays, volunteering, and personal time) • paid leave for parents and caregivers • a retirement savings plan • wellness support • health benefits including medical, prescription drug, dental, and vision coverage