David Chelimo

I work at the intersection of clinical diagnostics, cancer genomics, and data workflows. At Labcorp, I support clinical NGS assays through variant review, QC, and continuous improvement of bioinformatics workflows in a high‑throughput, regulated environment.

Previously, I helped build and scale the Genomic Analysis and Reporting (GAR) function at Foundation Medicine, curating ~95,000 samples and leading advanced analyses across complex cancer cases. Alongside that, I spearheaded adoption of agentic coding practices and AI coding assistants (e.g., Claude Code) to make our team’s development and maintenance work faster, safer, and easier to share.

My next step is to deepen my software engineering skill set and own more of the pipeline and tooling layer — building reproducible, well-tested, AI‑assisted workflows that bridge clinical bioinformatics and software engineering.

• Support clinical NGS assays through variant review, QC, and troubleshooting in a high‑complexity diagnostic setting.
• Contribute to workflow improvements and documentation to enhance reliability, reproducibility, and turnaround time.
• Collaborate with cross‑functional teams to align assay needs with data and tooling requirements.

• Led advanced analysis and delivery of NGS data in a high‑complexity clinical diagnostic laboratory as part of the Genomic Analysis and Reporting (GAR) team.
• Developed annotated genomic profiles and reviewed complex somatic variant calls for cancer patients across a broad range of tumor types.
• Implemented process improvements, including database search features and automation tools for bioinformatics workflows (Python, SQL, internal tooling).
• Spearheaded adoption of agentic coding practices and AI coding assistants (Claude Code): designed team training, established multi‑step prompting patterns and validation steps, and integrated AI‑assisted coding into development and maintenance workflows.
• Mentored junior analysts and presented findings to collaborators and internal teams.

• Developed annotated genomic profiles of somatic aberrations based on NGS data in cancer‑patient samples.
• Reviewed genomic variant calls using IGV and proprietary tools in collaboration with scientific teams.
• Delivered clinical reports in compliance with SOPs and defined turnaround times.
• Contributed to tools and workflows that improved efficiency and robustness in bioinformatics operations.
• Participated in training new team members and contributed to internal documentation.

• Designed and led internal training for the Genomic Analysis and Reporting (GAR) team on using AI coding assistants (Claude Code) for day‑to‑day development.
• Established agentic coding workflows: multi‑step prompting, tool‑using patterns, validation strategies, and code‑review practices to keep AI‑generated outputs safe and maintainable.
• Helped teammates adopt AI‑assisted refactoring, test generation, and documentation, accelerating development, deployment, and maintenance of internal tools and scripts.

• Built Python scripts to automate routine QC checks (coverage thresholds, call flags, file validation), reducing repetitive manual review in clinical pipelines.
• Introduced configuration files, logging, and lightweight tests to make utilities easier to maintain and reuse across the team.
• Used AI coding assistants to draft and refactor sections of code while maintaining strict validation and review steps throughout.

• Created assay performance and operations metrics for scientific and business stakeholders, highlighting trends and improvement areas.
• Summarized complex genomic data into clear visuals and narratives to support decisions on assay health, validation, and process optimization.