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Unlearn AI

AI-powered patient digital twins for simulations

Senior Clinical Data Scientist

Quantitative Biology & BiostatisticsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • A BS or advanced degree in Bioinformatics, Computer Science, Psychology, Public Health, or a related discipline.
  • At least five years of experience wrangling data from disparate sources, cleaning data, and harmonizing datasets for analysis.
  • Experience working with complex or nuanced datasets.
  • Fluency in Python and its essential data science tools, including NumPy and pandas.
  • Demonstrated experience in collaborative software development.
  • Experience with clinical datasets in applied machine learning applications.
  • Experience working in multidisciplinary teams that include scientists, engineers, and product management.
  • Prior experience in forward-deployed, client-facing settings.
  • Experience in clinical or healthcare data.
  • Experience with regulatory-facing clinical data standards such as CDISC, ADaM, and SDTM.

Responsibilities

  • Transform clinical trial, observational, and electronic health record data into high-quality, well-structured datasets.
  • Evaluate data quality, bias, and limitations, and proactively propose mitigation strategies.
  • Analyze longitudinal clinical datasets and develop a strong understanding of outcome measures, biomarkers, and other variables commonly used in clinical research across multiple disease areas.
  • Collaborate with cross-functional teams of data scientists, machine learning scientists, engineers, and clinicians to design, build, and maintain robust data products grounded in sound data organization, domain knowledge, and careful analysis.
  • Communicate technical findings, data characteristics, and limitations clearly to internal partners and external collaborators, including in forward-deployed, client-facing settings.

About the Company

Unlearn AI

AI-powered patient digital twins for simulations

Unlearn.AI builds AI-powered digital twins of patients to simulate health outcomes and predict how a patient’s condition may evolve over time. Its platform uses patient data to generate virtual replicas and run treatment scenarios to forecast results and guide care decisions. The technology can model control groups in clinical trials, potentially speeding drug development and reducing the number of real participants. The company uses a service/subscription model, charging providers and pharmaceutical partners for access, with the aim of improving trial efficiency and lowering healthcare costs.

Company size
51-200
Company stage
Series C
Total funding
$130.7M
Headquarters
San Francisco, CA
Founded
2017

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