Senior Manager, Data Science
Company: Bristol Myers Squibb
Location: Hyderabad
Department: Digital Health – Data Science & Advanced Analytics
Level: Senior Manager
Job Type: Full-Time
Travel Requirement: Less than 10%
Role Summary
The Senior Manager, Data Science is a highly technical, hands-on individual contributor role focused on developing advanced analytics and machine learning solutions using wearable and sensor-generated health data. The position involves building end-to-end data science pipelines, from raw signal processing to validated predictive models, supporting digital health initiatives and clinical research programs.
The role requires extensive coding, model development, validation, and collaboration with clinical, statistical, engineering, and product teams.
Key Responsibilities
Wearable & Sensor Data Analytics
Build and maintain Python-based pipelines for wearable and sensor-derived time-series data.
Perform:
Data quality control (QC)
Signal preprocessing
Artifact detection and removal
Missing data imputation
Feature engineering
Analyze longitudinal physiological datasets including:
Accelerometry
Actigraphy
Heart Rate Variability (HRV)
Oxygen Saturation (SpO₂)
Signal Processing & Feature Development
Develop algorithms for:
Signal detection
Digital filtering
Frequency and time-frequency analysis
Create clinically meaningful biomarkers and physiological measures.
Characterize disease progression and patient subtypes using digital health data.
Machine Learning & AI Development
Develop and validate predictive models using:
Deep Learning
Transformer Architectures
Ensemble Models
Representation Learning Techniques
Apply explainable AI methodologies where appropriate.
Optimize model performance and reliability for clinical applications.
Statistical Analysis
Apply advanced longitudinal statistical techniques:
Mixed Effects Models
Hierarchical Models
Repeated Measures Analysis
Handle missing data and within-subject variability using robust statistical methods.
Validation & Reproducible Research
Implement rigorous model evaluation frameworks:
Nested Cross Validation
Leave-One-Out Validation (LOO)
Out-of-Bag (OOB) Validation
Develop reproducible workflows and maintain high-quality documentation.
Ensure code quality, scalability, and regulatory readiness.
Cross-Functional Collaboration
Partner with:
Clinical Teams
Biostatistics Teams
Data Engineering Teams
Product Teams
Review and validate outputs from external vendors and analytics partners.
Participate in technical discussions and scientific decision-making.
Technical Leadership
Conduct code reviews and promote software engineering best practices.
Mentor team members on analytics methodologies and coding standards.
Drive continuous improvement in data science processes and technical rigor.
Required Qualifications
Education
PhD (Preferred) or
Master's Degree with significant experience in:
Data Science
Biostatistics
Biomedical Engineering
Computer Science
Related Quantitative Discipline
Technical Skills
Strong Python programming expertise.
Experience building production-quality analytics pipelines.
Advanced machine learning and deep learning knowledge.
Time-series analytics and signal processing expertise.
Statistical modeling of longitudinal clinical data.
Experience working with wearable or digital health datasets.
Uttar Pradesh :
Agra | Gajraula | Gautam buddha Nagar | Ghaziabad | Gorakhpur | Greater Noida | Jhansi | kanpur | Lucknow | Mathura | Noida | Park City | Prayagraj | Satyamev | Varanasi |Gujarat :
Ahmedabad | Ankleshwar | Baroda | Bharuch | Gandhinagar | Gujarat | Halol | Jhagadia | Mehsana | surat | Tarasadi | Vadodara | Vapi |Maharashtra :
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Hajipur | Patna |Kerala :
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Remote, India | Siliguri |Illinois :
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Norway | NOrway |Romania :
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China | Quarry Bay |Liaoning :
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Sweden |Taipei :
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Warsaw |