D. in a relevant discipline (Data Science, Machine Learning, Electrical/Industrial Engineering, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline); Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages; Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls; Intermediate proficiency in machine learning algorithms and concepts; Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen; Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders. Key Working Relationships: Active member of the Data Science community to build personal acumen and ability while sharing best practices with others; Builds relationships and networks within the current function, with guidance as needed to expand networks cross‑functionally; Interacts most often with Bioinformaticians and Data Scientists within the organization and peer business partners; Reports to a Precision Genomics Analytics & Insights Lead but independently drives data science projects with key stakeholders spanning functions and countries.