Sr Data Scientist (Computational Biology)
Informatics | San Francisco, Ca | Full Time
Senior Data Scientist
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. www.parkerici.org
Overview of the Role
The Senior Data Scientist (Computational Biology) will lead data analysis projects at PICI, including both PICI clinical trial projects and collaborations with partners. The shared goal of these projects analyzing molecular and clinical data to uncover novel insights leading to mechanistic discoveries, patient selection biomarkers, or new therapies. The Senior Data Scientist (Computational Biology) 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 Senior Data Scientist will perform primary Senior Data Scientist (Computational Biology) processing of molecular data and then marry molecular and clinical data to uncover novel insights.
The Senior Data Scientist (Computational Biology) will be expected to mentor more junior team members and lead their work on projects. For the right candidate, this could be a management role with 1-3 direct reports, or could grow into a management role with time.
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 project delivery. Lastly, they will need to be a strong scientific leader, capable of driving the scientific direction of multiple projects and influencing the scientific direction of the PICI organization as a whole.
Reporting Structure and Team
The Senior Data Scientist (Computational Biology) reports to the Director of Informatics and is a key member of the Informatics team. The Senior Data Scientist (Computational Biology) will also work closely with the Translational Medicine and Research teams.
FLSA Status: Exempt
Essential Job Functions
- Lead analysis projects for PICI clinical trials or data collaborations with pharma partners. This includes setting the scientific project direction, managing the work of other team members, communicating with stakeholders, and taking responsibility for project delivery.
- Lead production of conference presentations and publications.
- Mentor or manage (depending on experience) more junior scientists.
- Work closely with Translational Medicine and Research groups to determine questions of interest, set scientific direction, and refine results.
- 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.
Knowledge, Skills, and Experience
- PhD in Bioinformatics, Statistics, Biology, or related discipline
- 3+ years post-doctoral work experience in academia or industry
- 8+ years’ experience analyzing data in an academic or industry setting
- Strong programming skills in R
- Strong publication record in immuno-oncology, translational medicine, immunology, cancer biology, or related field
- Strong knowledge of two or more molecular data types (sequencing, gene expression, flow/CyTOF, tissue imaging, or related)
- Experience with ggplot2, seaborn, matplotlib, or related visualization libraries
- Experience with command line tools and cloud computing
- Strong knowledge of statistical concepts relevant to translational research (hypothesis testing, survival analysis, regression, etc.)
- Experiencing mentoring or managing junior scientists
- 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:
- Experience with management (a management role could be available)
- Experience working in a pharma or biotech industry setting
- Experience at the bench running flow/CyTOF, imaging, or sequencing assays
- Experience in Immuno-Oncology
- Experience with clinical research
- Experience with database technologies