Bioinformatics Scientist

Tempus AI•Redwood City, CA

1d•$100,000 - $175,000•Remote

About The Position

Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. We are seeking a highly motivated and capable Bioinformatics Scientist to join our Liquid Biopsy Science team. This role will focus directly on assay and algorithmic development, optimization, and analytical validation of our next-generation Liquid Biopsy assays. The ideal candidate will possess deep technical and biological expertise to address key liquid biopsy challenges for various applications including diagnostics, complete genomic profiling, therapeutic selection, and treatment response monitoring (TRM).

Requirements

Must have completed a Ph.D. or a Masters with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
In-depth knowledge of modern tools and pipelines for processing, aligning, and analyzing multimodal NGS data (including epigenetics, DNA, RNA).
Computational skills using Python and/or R, including experience with data science and biological computing libraries.
Expertise with cloud computing environments (AWS or GCP), container solutions (Docker), and common workflow management tools (Nextflow, Snakemake)
Proven scientific reputation as demonstrated by scientific publication and/or contribution to successful product development in industry
Strong background in constructing statistical models, creating predictive/prognostic algorithms, and applying machine learning techniques.
Demonstrated effective communication and presentation skills
Self-driven and works well in interdisciplinary teams

Responsibilities

Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data to detect oncology related biomarkers (SNV/indel/CNV/rearrangements, MSI, bTMB) from cell free DNA.
Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation and tracking, enabling robust evaluation for longitudinal treatment response monitoring (TRM).
Improve advanced molecular barcoding filtering strategies to distinguish true low-frequency oncology-related biomarkers from background sequencing artifacts.
Design and integrate machine learning classifiers and filtering logic to effectively differentiate non-tumor-derived Clonal Hematopoiesis variants from true tumor-derived variants, protecting patients from inappropriate therapy selections.
Design and execute experiments to evaluate the assay’s analytical performance to support regulatory documentation for CAP/CLIA, New York State (NYS), FDA, and MolDx submissions.
Work closely with wet-lab assay development scientists, medical directors, clinical scientists, biostatisticians, software engineers, and product managers to translate cutting-edge research into clinically actionable insights and production-scale pipelines.