[Hiring] Cancer Genomics Data Scientist @TESA RESEARCH

Role Description

TESA Research is seeking a Cancer Genomics Data Scientist to identify, retrieve, and prepare genomic and clinical data from public and proprietary sources for use in TESA's proprietary software platform. This role works in close collaboration with the VP of Cancer Genomics and can draw on the software engineering team for platform-level support, but is expected to independently perform the core data identification, extraction, and transformation work that feeds the platform. This is a hands-on, detail-oriented role for someone who is comfortable working across public repositories, proprietary datasets, and internal tooling to get data analysis-ready.

Key Responsibilities

• Data Acquisition: Identify and download relevant genomic and clinical datasets from public repositories (e.g., TCGA, GEO, cBioPortal, SRA, ICGC) and proprietary/licensed databases.
• Data Preparation & Transformation: Clean, curate, harmonize, and format genomic and clinical data so it is compatible with TESA's proprietary software platform, independently handling the majority of data transformation work.
• Pipeline Execution: Run and manage DNA and RNA analysis pipelines (e.g., alignment, variant calling, expression quantification) to generate processed datasets ready for downstream analysis.
• Platform Loading & QC: Load prepared datasets into TESA's platform, verify data integrity and formatting, and troubleshoot discrepancies before results are generated.
• Scientific Collaboration: Work closely with the VP of Cancer Genomics to understand data and analysis requirements, prioritize datasets, and ensure outputs support the company's scientific objectives.
• Cross-Functional Support: Partner with the software engineering team on platform-related data ingestion issues, flagging technical blockers while independently resolving data-level issues.
• Documentation: Maintain clear documentation of data sources, provenance, transformation steps, and pipeline versions to ensure reproducibility and auditability.

Qualifications

• Advanced degree in Bioinformatics, Computational Biology, Genomics, or a related field; PhD preferred
• Hands-on experience with DNA and RNA analysis pipelines (e.g., differential expression analysis, GSEA, CNV calling, ASCAT)
• Experience working with public and proprietary genomic and clinical data repositories
• Solid understanding of cancer genomics and the structure of associated genomic/clinical datasets
• Proficiency in scripting/programming for data wrangling (e.g., Python, R, or equivalent) and command-line bioinformatics tools
• Ability to work independently on data transformation tasks while collaborating effectively with scientific and engineering colleagues
• Strong attention to detail and comfortable working in a fast-moving, resource-conscious early-stage company environment

Requirements

• Experience preparing data for a proprietary or internal software/analytics platform
• Familiarity with cytogenetic or pathway-level data and their integration with genomic datasets
• Experience with cloud-based or high-performance computing environments for large-scale genomic data processing
• Prior experience in a startup or small-team research environment

Benefits

• Meaningful equity ownership in an early-stage company with high growth potential
• Competitive base salary commensurate with experience and company stage
• Significant autonomy and flexibility in how and when you work
• Direct influence over company strategy and direction as a member of the founding/early leadership team
• The opportunity to build something from the ground up and shape the scientific direction of a growing cancer genomics company
• Formal benefits package to be established as the company scales