The Opportunity
Key to insitro’s approach to rethinking drug development is leveraging disease models, genetics, and clinical datasets to link in vitro and cellular phenotypes with patient outcomes.
Multimodal clinical datasets are an essential component of modeling patient heterogeneity, disease progression, and phenotypic diversity. Our goal is to develop sophisticated models from patient clinical records, common lab biomarkers, and, when available, high-content multi-omic and imaging data to identify coherent patient segments to reveal novel genetic signals and opportunities for targeted therapies.
As a clinical machine learning scientist, you will develop, productionize, and deploy cutting-edge ML approaches to analyze and integrate large-scale multi-modal phenotypic datasets, including electronic health records, physiological monitoring, longitudinal clinical data, biomarkers, and multi-omic modalities. You will work with clinical data from large human cohorts such as randomized clinical trials, electronic health records, national biobanks, and other sources. You will contribute to developing models to understand patient state and predict outcomes and clinical endpoints. You will collaborate with a cross-functional team of machine learning scientists, statistical geneticists, life scientists, and clinicians to identify therapeutic targets and develop drugs that have high efficacy and low toxicity. You will work in collaboration with the software engineering team to ensure these pipelines are robust, reusable platform components that can be deployed on large-scale datasets in a portable way.
You will be joining a vibrant biotech startup that has long-term stability due to significant funding, yet is in a high growth phase. A lot can change in this early and exciting phase, providing many opportunities for 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! This role is preferably based in San Francisco Bay Area or Boston, but we are open to discussing other locations in the United States and the UK.
About You
- Ph.D. in biomedical informatics, machine learning, computer science, or a related discipline, or equivalent practical experience (e.g., a Masters degree plus 2 years in relevant industry experience);
- Demonstrated ability to use cutting edge statistical and machine learning methods for analyzing clinical data;
- Extensive hands-on experience working with at least one of the following areas: real-word data such as electronic health records (EHR/EMR), insurance claims, or clinical trial data; disease progression modeling;
- Demonstrated ability to rigorously identify and deal with confounders and complexities in human clinical data;
- Proficiency in Python or R;
- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions;
- Passion for making a difference in the world.
Nice to Have
- Experience with association testing, statistical or causal inference, and uncertainty evaluation;
- Experience with natural language processing (NLP) on real-world data, especially deriving features from unstructured clinical notes, phenotype ontologies, or other text containing medical terminologies;
- Experience with longitudinal data, time series analyses (e.g. data from wearable devices);
- Experience with genomic data (e.g. RNA-seq, proteomics, metabolomics, methylation, etc.) or biomedical/biophysical imaging modalities;
- Experience using modern deep learning frameworks (PyTorch, Jax, XGBoost, etc);
- Familiarity with cloud computing services (e.g., AWS or GCP) and workflow management tools or batch scheduling systems (e.g. SLURM);
- Proficiency in Linux environment (including shell/Bash scripting), experience with database languages (e.g., SQL) and experience with version control practices and tools (e.g., Git)
Compensation & Benefits at insitro
Our target starting salary for successful US-based applicants for this role is $160,000 - $215,000. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, the level at which they are actually hired, 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), 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
About insitro
insitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic state based on human cohort data and in-house generated cellular data at scale. These predictive models can be brought to bear on key bottlenecks in pharmaceutical R&D to advance novel targets and patient biomarkers, design therapeutics, and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of biologic insights and molecules in neuroscience and metabolic diseases. Since formation in mid 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 the company’s website at www.insitro.com .