Specialist, Data Science & Artificial Intelligence

IN10 (FCRS = IN010) Novartis Healthcare Private Limited; Hyderabad; On-site; INR 900,000 - 1,200,000; Full time

Job summary

IN10 (FCRS = IN010) Novartis Healthcare Private Limited in Hyderabad, India, invites a data‑science specialist to develop mechanistic, empirical and ML models for drug product formulation and process development.

You will build end‑to‑end data science solutions, prepare data, run experiments, and deliver transparent analyses with clear visualizations and narratives for diverse stakeholders.

Qualifications

• Master’s degree or PhD in a quantitative engineering discipline or data science.
• 2–4 years of relevant industry experience after master’s, or 0–4 after PhD.
• Strong foundation in process science, transport phenomena, statistics, numerical methods, or mechanistic modeling.
• Hands-on programming experience in Python.

Responsibilities

• Develop and apply modeling approaches to support drug product formulation and process development.
• Translate questions into model-and-data-ready problem statements with SME input.
• Build predictive models and decision-support tools for unit operations; focus on oral solid dosage forms and process engineering.
• Create end-to-end data science solutions from data preparation to deployment and lifecycle management.

Skills

Biostatistics

Data Visualization

Machine Learning

Data Governance

Statistical Analysis

Time Series Analysis

Communication skills

Education

Master's or PhD in quantitative engineering/data science

Tools

Python

gPROMS

Job description

Job Description Summary

• Understands business problems, supports an integrated analytical approach to mine data sources, manage data effectively, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs, discover actionable insights, and automate processes for reducing effort and time for repeated use.
• Provide data science and quantitative analytical support by ensuring the timely delivery of high-quality reports.
• Build capabilities to leverage the Science of data.

Job Description Major Accountabilities

Develop and apply mechanistic, empirical, statistical, and hybrid modeling approaches to support drug product formulation and process development, especially for process understanding, scale-up, and manufacturing‑relevant questions. Translate formulation and process questions into model‑and data‑ready problem statements; define success criteria, assumptions, and uncertainty considerations with subject‑matter experts. Apply statistics, Design of Experiments, multivariate analysis, and data‑driven modeling to plan experiments, analyze results, and accelerate learning cycles. Build predictive models and decision‑support tools for key drug product unit operations, with particular interest in oral solid dosage forms, powder technology, formulation, and process engineering. Build end‑to‑end data science solutions including data preparation, exploratory analysis, modeling, validation, deployment, and lifecycle management, with a focus on transparency and reproducibility. Create clear visualizations, dashboards, and technical narratives to communicate insights and support decision making for diverse stakeholders. Contribute to automation and AI‑assisted workflows for data preparation, modeling, analysis, and reporting, while maintaining scientific oversight and practical usability. Contribute to knowledge sharing, documentation, internal standards, and reusable modeling/AI assets within the global modeling and digital community.

Essential Skills

Master’s degree or PhD in mechanical engineering, process engineering, chemical engineering, pharmaceutical engineering, materials science, applied mathematics, statistics, data science, or a closely related quantitative engineering discipline. Early‑career profile preferred, typically with 2–4 years of relevant industry experience after a master’s degree or 0–4 years after a PhD, and a clear motivation for hands‑on modeling, coding, and applied problem solving. Strong engineering and mathematical foundation, including process science, transport phenomena, statistics, numerical methods, and/or mechanistic modeling. Must have hands‑on programming experience in Python or a similar programming language, with the ability and motivation to become productive in Python very quickly if not already fluent. Experience applying statistics, DoE, data analysis, simulation, optimization, and/or machine learning to engineering or scientific problems. Ability to work with experimental and industrial datasets, including data cleaning, exploratory analysis, and uncertainty‑aware interpretation including model credibility assessments according to regulatory guidelines & standards. Strong communication skills to explain technical concepts to non‑experts and influence decisions.

Desirable Skills

Experience or academic exposure to powder technology, formulation science, oral solid dosage forms, pharmaceutical unit operations, process modeling tools, PBM, DEM, gPROMS, or digital twins. Exposure to QbD principles, PAT concepts, or regulatory‑relevant modeling activities. Experience working in global matrix organizations.

Skills Desired

Biostatistics, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Statistical Analysis, Time Series Analysis