Principal Computational Scientist, Immuno-oncology Biomarker

Boehringer Ingelheim is seeking an innovative computational biologist (Principal) level to drive discovery of First-in-Class drugs to treat cancer. This position is a unique opportunity to directly contribute to development of new therapeutics and work with industry leaders in broadening your skillsets in cancer biology, genetics, omics, biobanks, RWE (Real World Evidence), and related computational biology methods including AI. It is also an opportunity to grow yourself in a team environment of feedforward (vs feedback), continuous improvement, and empowerment.

As a member of the Global Computational Biology and Digital Sciences (gCBDS) organization, the incumbent will work as a member of cross-functional project teams, contributing to or driving the discovery of First-in-Class or Breakthrough drugs for Oncology. You will leverage multimodal data relating to gene, protein, and metabolite measurements to drive the development of biomarkers for drug development. In addition to advancing the discovery of new therapeutics, with immediate focus in the field of cancer immunology, the successful candidate will contribute to the identification and establishment of external collaborations that will deliver on the aforementioned goals. He/She will help develop and champion the use of multimodal data and emerging approaches including ML/AI to accelerate new therapeutic concepts. Publishing in peer-reviewed journals and speaking at internationally recognized scientific conferences are encouraged with active support.

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development, and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

Duties & Responsibilities

• Build in silico capabilities to identify biomarkers for enabling immuno-oncology, using multi modal omics data and computational biology approaches.
• Lead multiple bioinformatics projects that make innovative use of both public and internal data to help identify biomarkers to advance targets, prioritize patient segments, and articulate those findings and observations to internal stakeholders.
• Drive hypothesis generation by applying computational biology approaches that includes machine learning/AI techniques, data integration, and biological knowledge.
• Build and/or implement new computational biology capabilities to translate biological data into insights to advance new therapeutic candidates.
• Help educate and train Boehringer Ingelheim colleagues in computational biology and related areas. Continue to develop scientific expertise, credentials, and drug development expertise by keeping abreast of relevant literature, by expanding scientific/technical knowledge.
• Contribute to the greater good, including departmental administration, scientific culture, and technical evaluation of in-licensing opportunities.

Requirements

• Ph.D. degree or equivalent from an accredited institution in biological, statistical, computational, or other quantitative science.
• Five (5) or more years of relevant experience in drug discovery or biomedical research environment after completing a doctoral degree, with at least two (2) years’ experience in drug discovery, strongly preferred.
• Deep hands-on experience in one or more areas pertaining to the computational investigation of biomarkers for target validation, pharmacodynamics, efficacy, or patient stratification. Experience with real world evidence tools (eg Flatiron, Optum etc) is a plus
• Experience in leveraging pre-clinical, real-world and clinical data for biomarker analysis in one or more relevant areas such as translational medicine/research, reverse translation, patient selection and stratification, clinical trial design, companion diagnostics, and development of preclinical/clinical biomarker plans..
• Several years of experience in independently leading computational biology-related projects using omics data.
• Is a recognized science and/or technology subject matter expert across BI with a sustained publication and external presentation record.
• Experience in leading matrixed project teams
• Demonstrated experience in investigating biomarkers in a drug discovery or development context.
• Experience mining, analyzing and exploring multiple omics modalities, specifically within the domains of genomic, transcriptomic, proteomic, or metabolomic datasets
• Demonstrated expertise in Python, R or other languages, together with data visualization frameworks ( eg , ggplot2, matplotlib etc)
• Broad knowledge of a wide set of computational biology tools
• Desire to learn basic statistics and ardent desire to apply them.
• A keen interest in continuous development and broadening impact, such as reading new papers, learning new techniques in machine learning/AI for biological problems.
• Excellent interpersonal skills with an aptitude to build strong collaborations across matrixed teams.
• Excellent communications skills with an ability to clearly articulate complex scientific concepts to both technical and non-technical stakeholders.
• She/he identifies new methodologies, protocols and/or test procedures that contribute to department and Discovery Research goals and proactively proposes creative solutions to department or Discovery Research leadership.
  

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