Principal Data Scientist Engineer

Position Summary You will lead the design and delivery of high-impact data science and AI solutions across teams in India. You will work closely with product owners, engineers and business stakeholders to turn complex data into clear decisions. We value technical depth, curiosity, collaboration and ethical thinking. This role offers visible impact, clear career growth and the chance to help GSK unite science, technology and talent to get ahead of disease together. This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:

• Lead end-to-end development of machine learning and AI solutions, from problem definition to validation and production deployment.
• Translate business questions into technical approaches and clear, actionable insights for non-technical partners.
• Build, evaluate and validate models using supervised, unsupervised and deep learning techniques.
• Partner with engineering and data platform teams to deploy, monitor and maintain models on cloud infrastructure.
• Mentor and coach data scientists and analysts to grow skills and strengthen team practices.
• Promote responsible, reproducible and well-documented AI practices, including model validation and bias awareness.

Why You You want to solve meaningful problems with data and see your work make a measurable difference. This role is offered as a hybrid position based in India, with a mix of office and remote work depending on team needs. You will own technical initiatives, shape cross-functional decisions, and grow into visible leadership opportunities. If learning, impact and collaboration motivate you, we encourage you to apply.

Basic Qualification

• Bachelor s or Master s degree in data science, computer science, statistics, mathematics, engineering or a related quantitative field.
• Minimum seven years of professional experience in data science, machine learning or a related role.
• Strong programming skills in Python and experience with libraries such as scikit-learn, PyTorch or TensorFlow.
• Practical experience with SQL and at least one cloud platform (AWS, Azure or GCP).
• Proven track record deploying models to production and collaborating with software engineering teams.
• Clear communicator who can explain technical work to non-technical stakeholders and present results with concise visualisations.

Preferred Qualification

• Hands-on experience with large language models or other generative AI techniques.
• Familiarity with MLOps or LLMops tooling for model monitoring, CI/CD and lifecycle management.
• Experience with retrieval-augmented generation, vector databases, or semantic search systems.
• Exposure to multi-modal models (text, image, audio) or computer vision workflows.
• Advanced degree (Master s or PhD) in a quantitative subject or demonstrable equivalent experience.
• Previous experience in healthcare, life sciences or other regulated industries.

Skills

Algorithms, Data Assessment, Data Cleansing, Data Preprocessing, Exploratory Data Analysis (EDA), Hypothesis Testing, Mathematics Modeling, Model Evaluation, Predictive Modeling, Probabilistic Modeling, Reliability Engineering, Statistical Analysis Techniques, Statistical Significance Testing Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.