This role can be Remote, based in Cambridge, MA or Seattle, WA

ABOUT THE TEAM

You will be an integral part of 2seventy’s Data Sciences team within the interdisciplinary Data Analytics Department, which is situated in Cambridge, Seattle, and remotely. We leverage cross-disciplinary expertise in computational biology, bioinformatics, data science, engineering, statistics, and disease biology to ensure that we learn everything we can from 2seventy’s clinical trials and to ensure that truly transformative therapies reach our patients. We do this by collaborating extensively. Within Data Analytics we collaborate with fellow data lovers from the Clinical/Biometrics, Manufacturing/Process Data, and Data Sciences Engineering teams; across 2seventy we collaborate with scientists from Oncology Research, Gene Editing, Preclinical & Translational Development, and Analytical Development.

Come work with us! We’re a highly engaged, collaborative, and inquisitive group of data-obsessed individuals that can’t help but rise to the challenge.

HOW YOU’LL SUCCEED

In this role, you will bring more TIME to cancer patients by supporting our early- and late-stage programs to accelerate progress across the cell therapy development pipeline.

For early programs, you will help identify promising cancer therapeutic targets and strategize how to pair them with novel potency enhancements, using both internal and public-domain genomic and immunological data resources.

For late programs, you will develop predictive models using clinical, drug product characterization, and molecular datasets to holistically understand patient responses and derive actionable insights.

Some key activities include:

• Data mining to analyze and interpret molecular, immunological, preclinical, manufacturing, and clinical datasets.
• Next-generation sequencing (NGS) analysis to support the engineering of active and specific gene-editing technologies.
• Communicate results effectively within the team and to external collaborators of all levels and backgrounds.
• Contribute to data and pipeline engineering efforts across research, clinical and manufacturing organizations.
• Working with teammates in Data Analytics to define and follow best practices in analysis, visualization, and data management.
• Proactively brainstorming new ways data sciences can impact research and clinical projects.
• Advocating for awareness, acceptance, and the adoption of advanced analytics and digital transformation across 2seventy.

WHAT YOU’LL BRING

• A passion for diving deep into the data and science to improve the lives of cancer patients.
• Demonstrated your ability to derive biological insights from complex genomic and/or immunological datasets.
• A PhD in engineering, computational biology/bioinformatics, data science, computer science, biostatistics, or a related quantitative field and 4 years of experience as a post-doc or in industry.
  
  • OR a Master's degree in above fields with 8 years experience applying advanced analytical methods to high-dimensional datasets and communicating results to diverse audiences.
• Expertise with R or Python and experience with Linux environments.
• Prior experience working in cloud environment e.g., AWS.
• Prior experience with next-generation sequencing data, such as bulk RNA-Seq, single-cell RNA-Seq, or WGS is required.
• Prior experience working with publicly available biological databases.
• Knowledge of core concepts in data science and applied statistics, such as model testing, regression, classification, and clustering methods.
• A commitment to reproducible research.
• Demonstrated yourself to be collaborative scientist who fosters open communication, mutual understanding, and cooperation between teammates.
• Experience working on complex and dynamic projects, making decisions under uncertainty, and dealing with shifting priorities.
• Prior experience in the fields of oncology, immunology, immunotherapy, or gene therapy is a plus, but passion for understanding the complex biological systems that give rise to the data is a must!
• Strong curiosity about emerging trends in data sciences, genomics, computational biology, and bioinformatics and enthusiasm to bring new concepts and approaches to the team.

Bonus:

• Prior experience with high dimensional flow cytometry (CyTOF) data.
• Previous experience working with pipeline workflow languages (e.g. CWL, Snakemake, WDL, Nextflow) and with developing and maintaining docker containers.
• Experience analyzing CRISPR or other genome editing screen datasets.
• Prior experience analyzing clinical trial data.