Bristol Myers Squibb Hiring Drive 2024: Bristol Myers Squibb Hiring Drive 2024 for its Senior Manager, Biomarker Data Scientist. Bristol Myers Squibb Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Ph.D. degree in a relevant quantitative field. if you are interested, please apply as soon as possible.
Company Name: Bristol Myers Squibb
Role: Senior Manager, Biomarker Data Scientist
Location: Hyderabad
Experience: 1+ years
Qualification: Ph.D. in a relevant quantitative field
Batch: Any
Job Type: Full Time
Salary: Best in Industry
Bristol Myers Squibb Hiring Drive 2024
Job Description:
- You will join a new cutting-edge Drug Development Data Science and Biomarker team to advance the global drug development process.
- We are looking for candidates with strong computational, statistical, and biological capabilities with a demonstrated track record of translating complex data into testable hypotheses and experience modeling multimodal (clinical, omics, real-world data) using the classical ML and Deep Learning algorithms.
- We are looking for hands-on state-of-the-art practitioners.
Requirements:
- Ph.D. in a relevant quantitative field (i.e. Computational Biology, Biostatistics, Statistics, Computer Science, etc.) and 1+ years of academic/industry experience or Master’s Degree in a relevant quantitative field and 3+ years of industry experience
- Strong experience in the analysis of data generated by one or more -omics or molecular assays is required
- Knowledge of molecular biology, understanding of disease pathways are preferred
- Strong experience in biomarker data analysis with data generated from clinical trials, or electronic health records
- Experience in modeling methods particularly in their application to pharma R&D Experience in the application of AI/ML, and proficient in SQL, Python, and R and cloud platforms
- Experience developing statistical and machine learning models on high dimensional and high throughput data for time to event data and longitudinal outcomes
- Perspective in leveraging innovative approaches to expedite drug development and address the complexities of emerging data
- Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects.
- Strong problem-solving and collaboration skills, and rigorous and creative thinking.
- Excellent communication, data presentation, and visualization skills.
- Capable of establishing strong working relationships across the organization
Responsibility:
- Develop and apply novel or existing computational methods for patient segmentation from multimodal clinical and omics datasets for various treatment modalities in partnership with Translational, Clinical and Statistical Scientists
- Partner with lead and protocol statisticians in writing, reviewing and executing protocols and statistical analysis plans (SAP) for biomarkers and diagnostics, highlighting the biomarker strategy for clinical drug development
- Execute biomarker analyses on datasets from BMS clinical trials and real-world data cohorts
- Perform relevant and innovative statistical analyses of high-dimensional (e.g. gene expression, sequencing) data generated by cutting edge technologies
- Execute and contribute to the scientific and statistical strategy of drug development, including development of predictive biomarker(s) and precision medicine
- Optimize and validate biomarker assays for clinical trial usage.
- Develop, implement, and apply state-of-the-art algorithms to address key business problems and drive the implementation of innovative statistical methods in support of biomarker strategy
- Formulate, implement, test, and validate predictive models and implement efficient automated processes for producing modeling results at scale.
- Responsible for collaborating with cross-functional teams, including but not limited to clinicians, data scientists, translational medicine scientists, statisticians, and IT professionals.
- Manage and coordinate resources to produce quality deliverables within timelines for competing priorities.
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