Principal Scientist, Discovery BioSciences – Integrative New Targets, Oncology

Bristol Myers Squibb • Needham, MA

8d • Onsite

About The Position

The Oncology Thematic Research Center at BMS is a key research and early development engine, responsible for the discovery and development of novel oncology therapeutics for patients. Centered at our state-of-the-art research sites in Cambridge and Seattle, scientists focus on novel targets and pathways for tumors that are refractory to current therapies. With a deep understanding of the causal human biology, we are able to leverage our multiple modality platforms to best match the modality to the mechanism and desired outcome. We are a fully integrated drug discovery through translational and early clinical development organization which exploits state-of-the-art in vitro, in vivo and ex-vivo models of Cancer biology and Immuno-oncology to identify and validate targets. We partner closely with colleagues in Translational Medicine, Informatics and Predictive Sciences and Early Clinical Development to generate biomarker and patient enrichment hypotheses to enable efficient decision making in early clinical trials. We are optimally positioned to complement the world-class translational expertise, biology and leading academic research centers in the area. Our Bristol Myers Squibb research site in Cambridge Crossing will help us continue to deliver on our mission, positioning the company and our scientists in the heart of a vibrant ecosystem of world-class science, innovation, and business opportunities. Position Summary: We are seeking a highly motivated and innovative AI/ML scientist with experimental cancer biology experience to lead efforts at the intersection of agentic AI, machine learning, functional genomics, and target discovery. In this role, you will identify, create, and validate datasets, and contribute to the development of advanced algorithms and agentic-based tools to discover new therapeutic options within Oncology. In close partnership with cross-functional teams, you will integrate outputs yielding from functional screens, diverse ‘omics and real-world data to identify and novel actionable insights for testing. This role offers a unique opportunity to transform new target identification by enhancing predictive and analytical capabilities to meaningfully accelerate oncology target discovery and improve patient outcomes.

Requirements

• Bachelor’s Degree 8+ years of academic and / or industry experience Or Master’s Degree 6+ years of academic and / or industry experience Or Ph.D. or equivalent advanced degree in the Life Sciences 4+ years of academic and / or industry experience
• PhD with 4+ years of experience or MS with 6+ years of experience in cancer biology with a strong scientific mindset and a solid foundation for the application of computational biology, systems biology, and statistical approaches.
• Strong understanding of analytical and computational approaches and methodologies for functional genomics, single cell and spatial ‘omics.
• Broad experience with generating and analyzing genomics, proteomics data and/or functional genomics datasets.
• Experience in executing target identification strategies including the design, implementation, and validation of targets from forward and reverse genetic and/or phenotypic screens by use of genome engineering techniques, molecular biology, and genetic perturbation (eg shRNA, CRISPR, degron tagging of endogenous loci) is required.
• Excellent communication and cross-collaborative skills, with the ability to operate effectively in fast-paced research environments and influence diverse stakeholders.
• Strong understanding of functional oncology targets such as mutated oncogenes as well as principles around identifying cell surface targets for modalities such as antibody-drug conjugates, T-cell engagers, multispecifics, and radioligand therapies.
• Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams and stakeholders.
• Proven history of contributions to the scientific community in the form of papers and/or conference presentations.
• Experience in applying AI/machine learning and statistical modeling techniques.

Nice To Haves

• Demonstrated expertise in uncovering mechanistic biology that best informs target modality for drug discovery efforts is preferred.

Responsibilities

• Drive high-quality data science that is grounded in deep understanding of biology/mechanisms by contributing, developing and pressure testing applied data science methodologies and approaches to identify new targets for oncology drug development.
• Co-develop, communicate, and execute a multi-disciplinary research strategy to enable and enhance innovation in the identification of Oncology new targets by incorporating identified datasets and validating hypotheses yielding from AI/ML approaches.
• Closely align with the Informatics and Predictive Science teams to drive a portfolio of data-science driven integrative New Target projects for Oncology, and drive collaborative innovation to inform large and small molecule inhibitor target modalities.
• Collaborate on the development and implementation of innovative machine learning algorithms, AI/foundation models, and platforms to enable the delivery and validation of novel target insights with the BMS IPS, AI/ML, and other technology-focused teams.
• Play a leading role in matrix teams centered around key technologies such as new leads and computational chemistry, genomics, proteomics, and spatial technologies.

Benefits

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life benefits include: Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
• Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
• All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree