Principal Data Scientist – DDSAI GD

Overview

Lead end-to-end delivery of integrated analytical solutions for defined clinical-development and trial-operations business problems within J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD), owning solution definition, delivery, adoption, and use-case outcomes using ML, GenAI, optimization, and RWD.

What you'll do

• Own the end-to-end definition, development, validation, deployment, and adoption of integrated data-science solutions for defined business problems.
• Lead predictive modeling, simulations, optimization, and GenAI applications for study feasibility, enrollment forecasting, country and site selection, protocol design, and operational planning.
• Apply clinical, operational, cost, and RWD, including EHR, claims, registries, and clinical-trial data, to generate evidence on patient populations, treatment pathways, feasibility, and operational risks.
• Lead RWD analytics that inform protocol feasibility, eligibility criteria, recruitment and retention, study design, comparative evidence, and external-control use cases.
• Develop LLM-enabled workflows for information extraction, protocol comparison, data harmonization, clinical-concept interpretation, and targeted workflow automation.
• Partner with clinical, operational, technology, and data stakeholders to frame questions, manage trade-offs, and translate outputs into adopted recommendations and measurable use-case outcomes.
• Apply model-validation, MLOps, documentation, privacy, data-quality, and responsible-AI standards; contribute reusable code, data assets, and technical patterns.
• Communicate methods, model outputs, assumptions, limitations, and decisions clearly to technical and nontechnical audiences.
• Mentor junior colleagues and strengthen delivery practices across project teams.

What you'll need

• Master's degree in computer science, engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or another quantitative discipline.
• At least 5 years of industry experience leading end-to-end delivery of data-science solutions using ML, predictive modeling, optimization, NLP, GenAI, or RWD analytics.
• Demonstrated experience defining, validating, deploying, and driving adoption of analytical solutions that inform clinical-development, clinical-operations, or real-world evidence decisions.
• Hands-on experience with structured and unstructured clinical, operational, or RWD data, including multimodal modeling and time-series or simulation methods.
• Proficiency in Python and SQL, modern ML, optimization, and LLM-development libraries, and reproducible MLOps practices.
• Strong communication, stakeholder-management, and technical-leadership skills.

Nice to have

• PhD (preferred).
• Experience in healthcare, pharmaceutical development, MedTech, clinical development, or clinical operations.
• Experience applying RWD methods to clinical-trial design, including target-trial emulation, propensity methods, survival analysis, or time-to-event analysis.
• Experience delivering analytical products or applications used by clinical or business teams.

Details

• Location: Hyderabad, Andhra Pradesh, India.
• Job Function: Data Analytics & Computational Sciences; Sub Function: Data Science; Category: Scientific/Technology.