Senior Computational Biologist

Probablygenetic
United States
Hybrid

Who this role is best for

A natural match if you have experience in genetic data analysis and bioinformatics.

Best fit for

  • Candidates with a PhD in statistical genetics and experience in genetic data analysis
    — “PhD in statistical genetics, computational biology, bioinformatics, or similar, plus 4+ years post-PhD in academia or industry”
  • Individuals who have developed or automated genomic data pipelines
    — “take over, improve and fully automate our in-house pipeline for genetic data analysis”
  • Professionals with a track record of causal gene mapping using rare variant burden tests
    — “Conduct association and causal gene mapping in a selected indication, incl. via rare variant burden tests”

Things to consider

  • The role expects a mission-driven mindset with a focus on patient impact
    — “Energized by our mission: develop new treatments for patients who have none”
  • The position requires in-office presence in San Francisco for at least part of the week
    — “Hybrid, flexible work with high-trust and autonomy”

How to stand out

  • Highlight projects involving multi-modal data integration and ML collaboration
    — “Partner with ML researchers on data preparation, multi-modal integration and shared evaluation”
  • Emphasize experience with public genetic resources like gnomAD or ClinVar
    — “Working knowledge of public human genetic and functional genomics resources (e.g. gnomAD, GTEx, Open Targets, ClinVar)”
  • Showcase ability to prioritize targets and inform experimental design
    — “Hand off prioritized targets to wet lab validation and inform in vitro experimental plans and priorities”
Pace · SteadyCollaboration · MediumAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • owning bio data pipelines and interpretation
  • prioritizing new data modalities
  • training ML models on multi-modal data
Typical background
PhD in statistical genetics, computational biology, bioinformatics4+ years post-PhD experience

Skills & requirements

Required

BioinformaticsGenetic Data AnalysisMachine LearningPythonWorkflow ManagersCloud-scale Genomic Data Resources

Preferred

Statistical GeneticsComputational BiologyBioinformaticsPublic Human Genetic And Functional Genomics Resources

Stack & domain

PythonSnakemakeCloud-scale Genomic Data ResourcesCollaborationProblem-solvingBioinformaticsAIDrug Development

About the role

Original posting from Probablygenetic via Ashby

ABOUT PROBABLY GENETIC

Probably Genetic is changing the lives of patients living with severe, complex diseases. Our data platform is used by drug developers and patient advocacy groups to develop and launch treatments for these patients. Our technology discovers undiagnosed patients online, analyzes their disease state using machine learning and at-home testing, and enables compliant communication with patients. In doing so, we help patients access diagnoses, clinical trials, and treatments as early as possible.

We are a tight-knit group of hard-working, ambitious problem solvers united by a mission greater than ourselves. We do well by doing right by patients. We are developing some of the most cutting-edge solutions in healthcare, and our roadmap is packed with innovations in bioinformatics, AI, and drug development. We have built a lean, all-star team to help us bring our vision to life, and we want you to be a part of it.

Probably Genetic has raised multiple rounds of funding from Silicon Valley’s best investors, including Threshold, Khosla, and Y Combinator, and offer competitive salaries, comprehensive benefits, and meaningful early stage equity.

ABOUT THE ROLE:

Probably Genetic has built one of the deepest phenotyped genetic disease cohorts in the U.S. by facilitating patients' access to genetic testing. We are now using this rich database for target discovery.

We're hiring a Senior Computational Biologist to own our bio data pipelines and interpretation end-to-end. . You'll take our data from QC through positive control recovery to novel, causal, direction-of-effect target hypotheses, and collaborate closely with our team on prioritizing new data modalities to collect.. In addition, your results will be used by our ML researchers to train ML models on multi-modal data and support target discovery. . This is a hands-on, first-of-its-kind role reporting to our VP of R&D.

WHAT YOU'LL DO:

  • Bio data processing and QC: take over, improve and fully automate our in-house pipeline for genetic data analysis
  • Run power analyses and use your insights to inform which phenotypes and indications we prioritize, how we scale our database, and which data modalities we collect
  • Prove our data and pipelines recover known gene-phenotype associations and approved target-indication pairs, and replicate them against public resources
  • Conduct association and causal gene mapping in a selected indication, incl. via rare variant burden tests, colocalization tests, and Mendelian randomization
  • Partner with ML researchers on data preparation, multi-modal integration and shared evaluation
  • Hand off prioritized targets to wet lab validation and inform in vitro experimental plans and priorities

WHO YOU ARE:

  • PhD in statistical genetics, computational biology, bioinformatics, or similar, plus 4+ years post-PhD in academia or industry
  • Proven track record (via shareable projects or publications) of hands-on experience in processing, analysing and interpreting genetic / genomic data; Working knowledge of public human genetic and functional genomics resources (e.g. gnomAD, GTEx, Open Targets, ClinVar)
  • Strong Python skills; experience with workflow managers (e.g., Snakemake) and comfortable working with cloud-scale genomic data resources
  • Enough ML fluency to collaborate closely, support data preparation and have productive discussions
  • Energized by our mission: develop new treatments for patients who have none
  • Bonus: target discovery or human genetics experience in biotech or biopharma; experience with genetic disease and/or disease-enriched cohorts; multi-omics (e.g., transcriptomics, proteomics)

AS WITH ALL NEW HIRES AT PROBABLY GENETIC, YOU WILL ALSO NEED TO BE:

  • A good person. We work with some of the most marginalized populations on the planet and empathy is key
  • Patient-focused and motivated to have a lasting, positive impact on humanity
  • Comfortable in a fast-paced, often ambiguous environment with rapid change
  • Action-oriented and excited to build a company from the ground up

WHAT WE OFFER AT PROBABLY GENETIC:

  • An engaging and supportive team all on a mission to improve lives
  • Fair and equitable compensation with competitive early-stage equity grants
  • Generous Flexible Time off policy, that we actually use
  • Parental Leave Benefits (12 weeks for both birthing and non-birthing)
  • Hybrid, flexible work with high-trust and autonomy
  • A bright, inviting, pet-friendly office in Downtown SF near transit
  • Company-sponsored team lunch every Thursday
  • A “work from anywhere” policy, up to 4 weeks a year
  • Regular team retreats in exciting destinations
  • Health Benefits including medical, dental, vision, therapy, FSA, and 401k
  • And so much more!

Probably Genetic is committed to fostering a welcoming and inclusive work environment for people of all genders, sexuality, ethnicity, socioeconomic background and life experiences. We urge candidates of all backgrounds to apply. If you require specific accommodations as you interview or consider working with us, please let us know.

Source: Probablygenetic careers (Ashby)

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