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.
Position Responsibilities:In the role as a Principal Scientist within Discovery BioSciences, the ideal candidate will:
- 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.
Basic Qualifications: - 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
Preferred Qualifications:- This position will be located at the Cambridge, MA site and will not have the ability to be located remotely.
- 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.
- Demonstrated expertise in uncovering mechanistic biology that best informs target modality for drug discovery efforts is preferred.
- 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.
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Compensation Overview:Cambridge Crossing: $156,180 - $189,252
The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee's work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.
Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/.
Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:
- 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.
*Eligibility Disclosure: The summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.
