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Senior / Staff Scientist, Statistical and Translational Genetics

South San Francisco, CA

The Opportunity

At the heart of insitro's strategy is the application of cutting-edge machine learning (ML) to biological data, both primary and clinical data as well as in vitro models, to discover and develop medicines that matter to patients. Key to this is the application of cutting edge machine learning and statistical genetics techniques to define novel disease-related traits and to assess the extent to which they drive or are associated with disease.

You will lead the integration of human genetics data with multidimensional phenotypic and omic data to identify and validate drug targets across our core therapeutic areas and within cross-functional teams. You will lead efforts in target discovery and translation, working both with technical ML and statistical genetics teams to enable novel discoveries, and with translational teams to develop associations into preclinical targets.

This is a remote role. Occasional travel to our South San Francisco offices may be required. You will be joining a vibrant biotech startup that has long-term stability, with significant funding, and in a high-growth phase, and you will have many opportunities to make a significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

Responsibilities

  • Apply best practices statistical genetics techniques to drive novel target discovery across our therapeutic areas
  • Collaborate with a multidisciplinary team consisting of human genetics scientists, statistical geneticists and other team members to design, execute and interpret genetics studies in multiple disease indications
  • Deep dives into targets of interest, disentangling correlated from causal associations
  • Close collaboration with therapeutic area heads to design follow up experiments, and to triage results from these experiments
  • Generate, summarize, contribute to the writing of scientific reports and present results in internal and external meetings to a variety of audiences
  • Contribute to formulating insitro's long-term therapeutic strategy in neuroscience, metabolic disease and oncology
  • Define and evaluate novel biomarkers and phenotypes from clinical datasets and ML workflows
  • Guide the use of cutting edge machine learning models and statistical genetics analyses in large-scale genetic human cohorts with rich and multi-modal phenotypic data in order to advance our therapeutic programs and guide in vitro disease model development
  • Lead efforts to relentlessly follow up on novel candidate targets with the goal of producing viable therapeutic interventions and identification of genetically-defined patient populations that might benefit from them

About You

  • PhD or MD/PhD in statistical genetics/genomics, bioinformatics/data science, computational biology, systems biology, machine learning, or equivalent
  • 7+ years experience in statistical and translational genetics, and work relating to target discovery with genetic and genomic datasets, in a role involving translational science or drug development with relevant industry experience
  • Track record of using unbiased, data-driven approaches integrating human genetics with diverse and multi-dimensional datasets
  • Demonstrated ability to execute human genetics studies delivering novel genetic findings and medically relevant gene discoveries in a team-based environment
  • Experience with key tools and techniques in statistical genetics, including phewas, e/pQTL analysis, fine-mapping, meta-analysis, PRS, pleiotropy analysis, Mendelian randomization etc.
  • Experience with scientific programming in Python/R/Linux, including expertise using numpy, scipy, bioconductor, or similar toolkits
  • Commitment to writing reusable code and documentation and familiarity with coding best practices (e.g. source control, unit testing)
  • Comfortable working independently as well as leading scientific teams and large-scale projects, with experience in goal setting
  • Strong communication and collaboration skills, the ability to work effectively with cross-functional teams and external partners
  • Experience working in a fast-paced and dynamic environment, with the ability to adapt to changing priorities and timelines

Nice to Have

  • Experience in at least one of our key therapeutic areas (metabolic disease, neurology/neurodegeneration, oncology) is preferred
  • Familiarity with high-content data modalities, such as transcriptomics (e.g., scRNA-seq), clinical imaging (e.g. digital histopathology), and/or spatial transcriptomics/proteomics
  • Experience with development and deployment of cutting edge machine learning methods
  • Experience with a least one workflow language (e.g. Nextflow, Snakemake, Redun)
  • Experience with distributed data processing environments (e.g. Spark, Hadoop)
  • Familiarity with cloud computing services (e.g. AWS or GCP)
  • A strong publication record of meaningful contributions to high-quality work in relevant computational biology, systems biology, life sciences, or biomedical journals

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $175,000 - $225,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

  • 401(k) plan with employer matching for contributions
  • Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees on our base plans), as well as mental health and well-being support
  • Open, flexible vacation policy
  • Paid parental leave
  • Quarterly budget for books and online courses for self-development
  • Support to occasionally attend professional conferences that are meaningful to your career growth and development
  • New hire stipend for home office setup
  • Monthly cell phone & internet stipend
  • Access to free onsite baristas and cafe with daily lunch and breakfast
  • Access to free onsite fitness center
  • Commuter benefits

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

 

#LI-Remote

About insitro
 
insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience, oncology and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.

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