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Data Scientist

Informatics | San Francisco, Ca | Full Time

Job Description

About Us

 The Parker Institute for Cancer Immunotherapy (PICI) is radically changing the way cancer research is done. Founded in 2016 through a $250 million gift from Silicon Valley entrepreneur and philanthropist Sean Parker, the San Francisco-based nonprofit is an unprecedented collaboration between the country’s leading immunotherapy researchers and cancer centers, including Memorial Sloan Kettering Cancer Center, Stanford Medicine, the University of California, Los Angeles, the University of California, San Francisco, the University of Pennsylvania and The University of Texas MD Anderson Cancer Center. The institute also supports top researchers at other institutions, including City of Hope, Dana-Farber Cancer Institute, Fred Hutchinson Cancer Research Center, Icahn School of Medicine at Mount Sinai, Institute for Systems Biology and Washington University School of Medicine in St. Louis.

By forging alliances with academic, industry and nonprofit partners, PICI makes big bets on bold research to fulfill its mission: to accelerate the development of breakthrough immune therapies to turn all cancers into curable diseases.

Help us create a world that doesn’t fear cancer. Join us.

 Overview of the Role

 The Data Scientist will contribute to analyses of PICI Clinical Trial data with the goal of uncovering novel insights leading to mechanistic understanding, patient selection biomarkers, or new therapies. The Data Scientist will work collaboratively with other Informatics and Translational Medicine team members to analyze molecular data from a variety of assays, including but not limited to RNAseq, Whole Exome Sequencing, TCRseq, high-dimensional flow cytometry, cytokine measurements, and high-dimensional tissue imaging. Using PICI’s CANDEL data platform, the Data Scientist will perform primary processing of molecular data and then marry molecular and clinical data to uncover novel insights.

 The Data Scientist will begin by working collaboratively with 1-2 other Data Scientists on specific clinical trial projects, with the opportunity to grow quickly into the role of project lead.  

 The ideal candidate will be a strong technical contributor, capable of working independently to analyze data and produce high-quality results. They will need to balance a mindset of scientific inquiry with a results-driven attitude suited to the quick pace of clinical trial delivery. Lastly, they should be a team player and quick learner, excited to learn to use new analysis tools as well as contribute to shared code.

Reporting Structure and Team

The Data Scientist reports to the Associate Director of Informatics and is a key member of the Informatics team. The Data Scientist will also work closely with the Translational Medicine and Research teams.  This position is located in the San Francisco office post COVID and we offer remote opportunities until the office staff returns.  

 FLSA Status: Exempt

 Essential Job Functions

  • Ingest and process molecular data from one or more assays (sequencing, flow/CyTOF, imaging, and more) using PICI’s established data processing and storage platform
  • Use R to explore data with a variety of methods, looking for associations between molecular features and clinical variables such as response, adverse events, or course of treatment
  • Contribute to a shared codebase of high-quality R code for repeatable molecular and clinical data analysis
  • Work closely with Translational Medicine group to determine questions of interest and refine results
  • Present results to stakeholders, including both internal and external meetings
  • Prepare content for conference presentations and publications

 Knowledge, Skills, and Experience

  • PhD in Bioinformatics, Statistics, Biology, or related discipline
  • 5+ years experience analyzing data in an academic or industry setting
  • Strong knowledge of one or more molecular data types (sequencing, gene expression, flow/CyTOF, tissue imaging, or related)
  • Strong programming skills in R or Python (R strongly preferred)
  • Experience with ggplot2, seaborn, matplotlib, or related visualization libraries
  • Knowledge of statistical concepts relevant to translational research (hypothesis testing, survival analysis, regression, etc.)
  • Publication record in immuno-oncology, translational medicine, immunology, cancer biology, or related field
  • Ability to communicate results to a variety of stakeholders, including technical and non-technical scientific audiences
  • Ability to work as a team player, respecting others and holding a “learner not knower” attitude
  • Ability to work independently in a multi-disciplinary environment
  • Bonus qualifications:
    1. Experience at the bench running flow/CyTOF, imaging, or sequencing assays
    2. Experience in Immuno-Oncology
    3. Expert knowledge of R
    4. Experience with command line tools, cloud computing, and database technologies
    5. Experience with clinical research