Senior Data Scientist - Computational Biology & Immunology

Location: Philadelphia Area
Job Type:

Janssen Research & Development is a world-class biotech and pharmaceutical organization committed to research and development of innovative therapies for diseases of great need. Janssen Immunology Research & Development focuses on improving the health and lifestyles of people with serious immunological and inflammatory conditions worldwide, and today has a leading portfolio of medicines to treat psoriasis, Crohn’s disease, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis, atopic dermatitis and ulcerative colitis.

Janssen Immunology recognizes data science plays an increasingly meaningful role in drug discovery and development, from target validation to improved patient selection and predictive molecular, imaging and digital end points. As such, Janssen Immunology is committed to building out a foundational new data science capability, harnessing novel developments in analytical technologies and processes, to power its portfolio and pipeline as well as improve its ability to survey the external landscape for positive relationships.

You will take a key role in crafting and executing the Janssen Immunology data science strategy as part of the Translational Data Science team. This team is responsible for the use of analytics and molecular data to study disease biology across immune-mediated diseases. You’ll not only take a driving role in designing computational approaches to analyzing molecular data but also in implementing insights through cross-functional collaborations with scientists in Discovery and Translational Medicine. As such, strong trainings in computational biology and traditional biology are critical as well as experience successfully combining the two.

You will possess a balance of deep technical background in both biology and computational biology. In addition, given the collaborative nature of this role, exceptional communication and collaboration skills and an excellent ability to establish relationships are also critical. Lastly, the you will work to build a culture of open and simple communication around computational approaches to studying biology to enable extensive partnership across the Immunology team and to grow the sophistication with which scientists incorporate analytics and human molecular data into their day-to-day activities.

Key Responsibilities

Contribute to and execute against the Immunology translational data science strategy to support portfolio decision-making, clinical trial design and pathway identification

Drive the deep exploration of pathways or molecular signatures identified in human molecular data from Janssen clinical studies

Collaborate across functions to turn computational insights into drug development impact

Explore emerging approaches to predicting important disease biology including methods for causal inference, machine learning or mining non-traditional data sources (e.g., scientific literature)

Identify key data sources that support immunology strategic needs and enable their internal use and interpretation with appropriate pipelines

Educate all levels of the Immunology team on critical computational biology approaches and advances to drive integration into critical thinking

Build strong relationships with the scientific community and external innovators to harmonize internal efforts with external collaborations and monitor external activities

Qualifications

2+ years post-academic industry experience

PhD. degree in Biology, Bioinformatics, Computational Biology, Genomics, Systems Biology or related discipline

Extensive experience gaining biological insights using computational approaches and high-dimensional biological data (e.g., transcriptomics, genomics, etc.)

Experiencing using coding languages (such as Python or R) to analyze biological data

Deep experience in the study of a specific area of cellular biology

Experience in wet lab techniques and the generation of biological data is a plus

Expertise in computational methods that enable functional interpretation of biological data including co-expression, causal inference, pathway enrichment, network analysis etc.

Exceptional communication and collaboration skills

Experience navigating a matrixed organization is preferred