Senior Data Scientist, Discovery BiologyDepartment:
DS/ML (Data Science/Machine Learning)Employment Type:
San Mateo, CA
Description The Role:
BigHat Biosciences is seeking an exceptional Senior Data Scientist (or experienced Data Scientist)* to accelerate our selection of therapeutic programs, discovery of drug targets, and program development. *At BigHat we believe in titles that are commensurate with skill set, relative organizational impact, and value contribution; more or less experienced candidates are encouraged to apply, with the understanding that responsibilities and title would adjust as appropriate.
- Development of novel statistical/ML methods that leverage a range of unique data types from the BigHat platform, our partners, and public sources to drive decisions on therapeutic target selection
- Identification and triage of therapeutic targets from bulk tissue and single-cell whole-genome sequencing, transcriptomic and proteomic data
- Prioritization of potential protein targets based on assessment of biological and clinical evidence, viability, and alignment with BigHat's unique platform
- Identification of areas of major therapeutic opportunity across a diverse set of diseases
- Leading computational and bioinformatic analyses that support the identification, development and assessment of therapeutic programs at BigHat
- Collaborating with scientists and program leads to quickly design, execute, and analyze experiments on the BigHat platform that guide our therapeutic programs
This role reports directly to the Data Science Lead; works closely with other executives and senior leaders, particularly our Chief Development Officer and our Director of Translational Research; and has broad responsibilities across BigHat for target discovery and program development.
Skills, Knowledge, and Expertise
- PhD in relevant domain [Computational Biology, Biology, Chemistry, Bioinformatics, Bioengineering, or similar] with 3+ years of industry experience preferred
- Experience with whole-genome sequence data, bulk and single-cell RNAseq data, and protein expression data including working with public data sources (e.g. TCGA, Human Protein Atlas, Human Cell Atlas, GTEx), and identifying gene signatures of disease.
- Experience working with cancer genomics data, particularly tumor-associated antigen expression
- Strong knowledge of the data science toolkit, including: classic statistical models (regression, ANOVA, random effects models), statistical testing, interactive data visualization in python/R or React, and AI/ML techniques (SVMs, deep learning).
- Proficient in Python, R, or similar programming languages.
- Proficient with cloud computing infrastructure like AWS and with version control like Github or Gitlab
- Excellent communication skills, experience interacting with diverse scientific teams
- The experience and judgment to operate/make key technical decisions independently
- Enjoys a fast-paced environment and executing across multiple projects