Principal Data Scientist

Role: Principal Data Scientist (Individual Contributor)

Experience - 14+ years

Job Location - Mumbai and Gurgaon

Role Overview

As a Principal Data Scientist (IC), you will be a senior technical authority responsible for solving the organizations most complex and high-impact analytical problems using advanced analytics, AI, and machine learning. You will operate with a high degree of autonomy, owning solution architecture and technical direction while influencing stakeholders through expertise rather than formal people management. This role is designed for seasoned practitioners who prefer deep hands-on contribution, technical leadership, and strategic impact without direct team management responsibilities.

What Youll Do

• Own and deliver end-to-end advanced analytics and AI/ML solutions for complex, ambiguous business problems.
• Translate executive-level business questions into well-structured analytical frameworks and scalable technical solutions.
• Serve as the technical authority on data science methodologies, model design, and solution architecture across initiatives.
• Design, develop, validate, and deploy production-grade ML models and data products at enterprise scale.
• Drive technical standards and best practices across modeling, experimentation, MLOps, and responsible AI through influence and example.
• Partner closely with product, engineering, and business stakeholders to embed models into workflows and decision systems.
• Communicate complex analytical insights clearly and persuasively to senior, non-technical stakeholders.
• Provide technical mentorship and code/model reviews for other data scientists without formal line-management responsibilities.
• Continuously evaluate emerging techniques, tools, and platforms to improve solution quality, scalability, and impact.

What Youll Bring

• Masters degree or PhD in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related quantitative field.
• 15+ years of overall professional experience, including 10+ years of deep, hands-on experience in data science, machine learning, AI, or advanced analytics.
• Expert proficiency in Python, R, SQL, and modern ML/data science frameworks.
• Extensive experience designing, building, and deploying scalable, production-grade data science solutions on cloud platforms such as AWS, Azure, or Google Cloud.
• Strong practical experience across a wide range of ML techniques, including regression, classification, clustering, NLP, computer vision, and deep learning.
• Hands-on exposure to large-scale data systems, feature engineering pipelines, MLOps, model monitoring, and lifecycle management.
• Deep domain expertise in financial services, including areas such as banking, payments, fintech, credit risk, fraud detection, AML, underwriting, or capital markets (or equivalent regulated sectors).
• Proven ability to balance deep technical execution with strategic influence, ownership, and accountability.