AI Biologist - Cancer Biology (Applications)

LatchBio

$120K — $180K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1+ years in cancer biology (basic, translational, or clinical) with hands-on analysis of multi-omic tumor data.
  • Proficiency in Python and/or R for VCF/MAF parsing and single-cell analysis methods.
  • Understanding of cancer-genomics standards (AMP, ASCO, CAP, etc.).
  • Ability to distinguish real biological signals from analysis artifacts and recognize assay limitations.
  • Strong written communication skills regarding technical decisions and uncertainties.

Responsibilities

  • Identify and analyze real-life cancer biology datasets for clinical relevance.
  • Establish reference analyses and scoring criteria for various conclusions in cancer biology.
  • Anticipate potential errors in reasoning by agents handling cancer data.
  • Test agents' capabilities in dealing with experimental variability and incomplete information.
  • Engage in cross-domain integration and apply long-horizon reasoning in research.

Benefits

  • Flexible working schedules focused on productivity.
  • Waterfront office with numerous perks, including free meals and snacks.
  • Active company culture with diverse clubs and team outings.
  • Emphasis on cross-domain learning and collaboration across teams.
Full Job Description
AI Biologist - Cancer Biology (Applications)

About the Role

Our work in Cancer Biology means measuring whether an agent can take a tumor case from raw molecular data to a real clinical decision. You'll identify real cancer-biology datasets and turn them into rigorous, deterministically-graded tasks.

Our benchmarks are agentic and cross-domain. Each task hands an agent the artifacts a cancer researcher would actually have and asks for a concrete conclusion. Your job is to establish defensible reference analyses and scoring criteria across conclusion types, the benchmark measures that span basic cancer biology to clinical outcomes. You'll anticipate where agents take plausible but wrong turns and test whether they can handle experimental variability, incomplete data, conflicting evidence, and mechanism-driven tradeoffs.

Our team emphasizes cross-domain integration and long-horizon reasoning.

Requirements
  • 1+ years personally working in basic, translational, or clinical cancer biology. Experience with hands on analysis of multi-omic tumor data hands-on somatic/germline variant calling and interpretation (WES/WGS/panel; MAF/VCF), copy-number and structural-variant analysis, mutational signatures, bulk and single-cell RNA-seq (cell-state annotation, subtyping), tumor-immune contexture (immune deconvolution, spatial transcriptomics, multiplex imaging), subclonal reconstruction, or functional-genomics screens (CRISPR/RNAi), or clinical research is highly preferred.
  • Proficiency in Python and/or R: VCF/MAF parsing, single-cell analysis (Scanpy/Seurat), gene-set scoring (GSEA/ssGSEA), immune deconvolution (CIBERSORTx), subclonal reconstruction (PyClone), statistical analysis.
  • Understanding of cancer-genomics standards: AMP/ASCO/CAP and ACMG/AMP variant tiers, ESCAT and OncoKB actionability levels, PAM50 and Consensus Molecular Subtypes, IFN-γ/T-cell-inflamed signature, consensus Immunoscore.
  • Recognize experimental variability, and assay limitations; distinguish real biological signal from pipeline or annotation artifact.
  • Strong written communication on technical decisions, uncertainty, and alternative interpretations.

Nice-to-Have
  • Familiarity with cancer-genomics resources and standards: TCGA/GDC, PCAWG, AACR Project GENIE, cBioPortal, OncoKB/CIViC/VICC, COSMIC signatures, HTAN, Human Cell Atlas, DepMap/Project Score, gnomAD/ClinVar, MSigDB.
  • Breadth across multiple conclusion types like: diagnosis, mechanism, clonal evolution, immune contexture, target nomination, actionability.
  • Prior work on benchmarks, task-based assessment, or deterministic grading.


Culture @ Latch

How we work. Genuinely flexible schedules - we just ask that you communicate when you're coming in later than usual. We care most about hard work and output. We're respectfully opinionated, it will always be us against problems, not each other. Optimize for each other's time and bring solutions, not just problems. You'll join a bench suited to your expertise, but we value cross-domain learning and interoperability across teams.

Office & Perks. Waterfront office near Oracle Park, 2x free daily meals, unlimited snacks, company outings most months, and team offsites. Plus a vibrant community: cycling, soccer, figure skating, boxing, run clubs, reading clubs, martial arts, music, game nights.

Compensation & Logistics
  • 1099 (or W8-BEN) contract, 40 hrs/week, no end date
  • Fully performance-based pay - OTE: $120K-$180K, uncapped upside. 2x quota = 2x pay.
  • 2-4 week paid ramp: full OTE during ramp
  • Remote (globally), hybrid, or onsite in SF (onsite preferred)
  • Work authorization: OPT visa holders only (not STEM Extension)
  • Onsite perks: 2x free meals/day, waterfront office (China Basin), monthly parking (based on availability)
  • Candidates with all of the above qualifications + proven management skills will be eligible for more senior positions

Interview Process

Timeline: We move fast: 8 - 12 days from submission to offer.
  1. Intro Screen - Technical Recruiter
  2. Take-Home Project - HackerRank
  3. Technical Interview - Member of Technical Staff
  4. Culture Interview - C-Suite
  5. Offer

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