About The Position

The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit. IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS. We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company. We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers. Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma. We seek a creative and passionate computational biologist with a strong background in clinical data analysis to join the Neuroscience, Immunology, and Cardiovascular (NIC) Translational Informatics team within Informatics and Predictive Sciences (IPS). In this role, you will use machine learning and advanced statistical approaches to analyze high-dimensional data from late-stage clinical trials and longitudinal patient cohort profiling. In support of an exciting late-stage NIC portfolio, your responsibilities will include patient subgroup stratification, biomarker discovery for treatment response and resistance, and mechanistic analyses to support life cycle management and indication expansion. You will also contribute to reverse translation, leveraging clinical insights to inform early research and drive bedside-to-bench innovation beyond the current portfolio. Your work will directly impact the development of novel therapies for patients with neurodegenerative and neuropsychiatric, autoimmune, and cardiovascular disorders.

Requirements

  • Bachelor’s degree with 6+ years of academic/industry experience, or Master’s degree with 4+ years of experience, or PhD with 2+ years of experience in computational biology or a related field

Nice To Haves

  • PhD from a recognized institution in a quantitative field such as computational biology or related
  • Experience analyzing clinical data from interventional clinical trials, including integration of structured clinical endpoints (e.g., ADaM/SDTM), biomarker data (e.g., lab measures), and longitudinal assessments to support pharmacodynamic analyses, as well as the identification of predictive, prognostic, or surrogate endpoint biomarkers.
  • Experience analyzing and integrating high-dimensional molecular datasets such as multi-omics (proteomics, RNA-seq), single cell (scRNA-seq), and spatial transcriptomics
  • Advanced hands-on knowledge of at least one high-level programming language such as R or Python for computational and reproducible research practices
  • Experience with modern AI-assisted coding tools and applying AI/machine learning approaches to translational research problems preferred
  • Track record (such as scientific publications) in driving and advancing research projects/programs with computational approaches
  • Strong oral and written communication skills

Responsibilities

  • Analyze high-dimensional datasets from late-stage clinical trials and multi-modal real-world datasets from commercial partners, pre-competitive consortiums, and public resources.
  • Work with diverse data modalities, including clinical data (ADaM/SDTM), high throughput proteomics (e.g., Olink), RNA-Seq, epigenetics, and multiplex flow cytometry.
  • Perform deep and innovative analyses of these data to build comprehensive understanding of disease mechanisms and patient heterogeneity, identify non-responders to standards of care with unmet medical needs, generate testable hypotheses for drug differentiation, combination strategies, and novel indication opportunities.
  • Optimize reverse translation through application of late-stage clinical data sets to inform early-stage clinical trials and the discovery pipeline, in close collaboration with teams across Research and Development, including bioinformaticians, statisticians, biologists, biomarker leads, and clinicians.
  • Communicate findings and recommend follow-up actions in multiple settings (including 1:1, seminars, and team meetings).
  • Participate in authorship of scientific reports and present methods and conclusions to publishable standards.

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.
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