Senior Scientist, CAR-T Biological Data Science

Warren, NJ, US
Oct 25, 2018
Required Education
Position Type
Full time
Other Locations:US- NJ- Warren


Celgene is a global biopharmaceutical company leading the way in medical innovation to help patients live longer, better lives. Our purpose as a company is to discover and develop therapies that will change the course of human health. We value our passion for patients, quest for innovation, spirit of independence and love of challenge. With a presence in more than 70 countries, and growing - we look for talented people to grow our business, advance our science and contribute to our unique culture.

Excited about using data science to make a real difference in the lives of cancer patients?

Celgene's Informatics and Predictive Sciences (IPS) department seeks a talented, collaborative computational researcher to drive application of statistical and machine learning methods to identify critical patient and manufacturing factors in cellular therapies that affect efficacy, potential toxicities, and product consistency. The successful applicant is expected to play a key scientific role in leveraging innovative computational analysis strategies across a variety of biological and manufacturing data sources to empower data-driven decisions in the development of next generation cellular therapies.

Reporting to the IPS lead for Cellular Therapy Informatics and Analytics, the successful candidate will work alongside Global Product Development Organization (GPDO) colleagues in New Jersey and Seattle, R&D colleagues in the Immuno-Oncology and Cellular Therapy Thematic Center of Excellence (IO/CT TCoE), and global IPS colleagues engaged in computational research into therapeutic mechanisms of action, efficacy in patient populations, and reduction of potential toxicities.

Key areas of initial focus will include the application of machine learning and pattern recognition approaches to identify robust relationships between aspects of the cell therapy manufacturing process, properties of the resulting therapeutic product, and clinical end points. The product properties in scope include molecular and cellular phenotypes, cellular functional assays, and clinical trial outputs. Algorithmic approaches involved will include supervised classification and regression, unsupervised learning and outlier detection, alongside data integration and biological interpretation methods.

The preferred candidate will have experience in analyzing high dimensional single cell sequencing or flow cytometry data sets . A key focus of this position will be to develop, implement, and optimize novel techniques for characterizing CAR T-cells throughout their manufacturing process, including high dimensional cytometry, single cell transcriptomics, and epigenetic profiling.

The position would suit an individual with scientific leadership potential and excellent communication and collaboration skills. Keen interest and hands-on expertise in the inter-disciplinary application of advanced analytical methods to life sciences and clinical datasets are imperative. Applications are encouraged from those looking to impact delivery of truly innovative and life-changing therapies for complex diseases of unmet medical need.

Responsibilities include but are not limited to:
  • Develop algorithmic and data-driven approaches aligned to cell therapy development objectives, including state-of-the-art methods from related fields.
  • Develop novel integrative analysis strategies for molecular profiling data sets including RNA-seq, ATAC-seq, immune sequencing, high dimensional flow cytometry, and single cell sequencing to define critical therapeutic attributes.
  • Engage directly with colleagues and as part of project teams focused on optimizing our manufacture of innovative cell therapies, lending analytics expertise to biological and technical subject matter experts as required.
  • Collaborate with IPS, IO/CT and GPDO colleagues in areas of synergy and integrate data and methods applied in other business functions.
  • Contribute to broader data analysis and predictive methods strategies across IPS as required, including assessment of third-party capabilities.
  • Present strategies, approaches, results and conclusions to a publishable standard.
  • Contribute to strategic collaborations with academic and commercial collaborators to benefit therapeutic programs.
  • Catalyze a predictive culture across the GPDO function, by demonstrating benefits of leading analytical research in key application scenarios.

Background experience & complementary knowledge:
  • Ph.D. in bioinformatics, computational biology, statistics, computer science, or related fields from a recognized higher-education establishment; alternatively, a Ph.D. in immunology or genetics with a very strong publication record demonstrating computational expertise and the ability to analyze high throughput datasets.
  • 6+ years post-doctoral experience with predictive analytical research in solving biological problems in academic, clinical, or biotechnology environments. Strong publication record demonstrating use of analytical methods to elucidate and drive decisions in complex research scenarios, with focus on pattern recognition.
  • Experience analyzing high dimensional cytometry or bulk and single cell sequencing data (e.g., flow cytometry, RNA-seq, ATAC-seq, immune sequencing).
  • Fluency in Unix Bash, R, and Python and collaborative development skills using version control systems (e.g. Git).
  • Experience with notebook-based reproducible analysis tools (e.g. Jupyter, R Markdown) preferred.
  • In-depth knowledge of contemporary techniques, paradigms, application scenarios, and frameworks in machine learning and data-mining (e.g. caret, scikit-learn, TensorFlow).
  • Background knowledge in aspects of molecular biology, cancer biology, and immunology and/or related bioinformatics and computational biology approaches preferred.
  • Proven problem-solving skills, collaborative nature, and adaptability across disciplines.
  • Ability to work independently and also as a member of a multidisciplinary and global analytical research team in a fast-paced environment.
  • Fluent verbal and written English language skills.



Celgene is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Celgene complies with all applicable national, state and local laws governing nondiscrimination in employment as well as employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must have authorization to work for Celgene in the U.S.