Data Science Lead, Research Analytics
Role details
Job location
Tech stack
Job description
As a Data Science Lead in Research Analytics, you'll drive analytics solutions that inform compound and antibody discovery for early drug platforms. You'll apply data science and machine learning to diverse datasets-imaging, gene expression, high-throughput screens, and sequencing (e.g., mRNA display)-to identify initial hits and establish early structure-activity relationships. Your work supports the organization's Digital Business Transformation and spans modalities including small molecules, peptides, biologics, and gene therapy. You'll collaborate across departments and with external partners, capturing insights for meta-analysis and communicating results within interdisciplinary teams., * Lead platform development of novel modalities such as peptides, impacting therapeutic projects with data-driven insights using analytics and machine learning on high-dimensional datasets conducted with complex biological assays (e.g. next-generation sequencing, cell-based assays, time-series assays, high-content assays, *-omics assays, etc.).
- Clear communication of outputs & results from analyses for all relevant stakeholders.
- Adapt and design data processes to support the capture and analysis of assay data and metadata and elevate platform data capability.
- Develop workflows that can be used by team members for routine data processing and analysis.
- Active collaboration with relevant stakeholders in function areas such as Discovery Biology, Translational Biology, Computational Chemistry, Protein Sciences and fellow data science teams & IT.
Requirements
Computer Science, Data Manipulation, Biology, Statistics, Data Science, Informatics, Analytics, * PhD in biological, chemical, or data science with strong skills & experience in informatics, statistics, or computer science and demonstrated delivery in the life sciences space
- 8+ years of hands-on experience with data types, file formats, and common metadata used in biology, including high-dimensional experiments such as imaging, or high-throughput experiments such as peptide/biologics display.
- 8+ of experience with machine learning on large / high dimensional datasets including data manipulation, wrangling, and analytics.
- 8+ Experience with machine learning on chemical, sequence, and/or biological features.
- 8+ years of experience with R and/or Python