Deputy Vice President - Data Science Job in Indiafirst Life

Deputy Vice President Data Science

Location: Mumbai

Function: Technology Digital and Data Sciences

Employment Type: Full Time

Role Overview

We are seeking a seasoned and innovative Deputy Vice President Data Science to lead cutting-edge AI and data science initiatives. The ideal candidate will drive the development and deployment of machine learning models, architect cloud-native AI platforms, and guide strategic transformation through advanced analytics. This role requires strong leadership, deep technical expertise, and the ability to collaborate across business and technology teams to deliver measurable impact.

Key Responsibilities

• AI & Machine Learning: Design, develop, and implement advanced machine learning models for predictive analytics, NLP, computer vision, and recommendation engines. Lead end-to-end AI project lifecycles, including model validation, productionization, and continuous optimization using frameworks like TensorFlow, PyTorch, and scikit-learn. Stay current with the latest developments in Generative AI, foundation models, and LLMs; evaluate and integrate them into solutions where applicable. Identify and prioritize AI use cases in collaboration with cross-functional teams to create business value.
• Data Science & Analytics: Lead the complete analytics lifecycle from data exploration and model building to insight generation and product deployment. Work closely with data engineers and analysts to develop scalable, high-impact solutions that influence business outcomes.
• Leadership & Strategy: Mentor and develop junior team members, promoting a culture of learning, experimentation, and excellence. Contribute to enterprise-wide AI and cloud strategies, including vision setting and roadmap development.
• Cloud Architecture & Engineering: Architect and implement cloud-native AI and data platforms on GCP (preferred), with working knowledge of AWS or Azure. Build and optimize scalable ML workflows and data pipelines using platforms like Vertex AI, SageMaker, or Azure ML. Ensure secure, scalable, and cost-effective infrastructure, supported by CI/CD pipelines and MLOps best practices.

Required Skills & Qualifications

• Technical Proficiency: Strong coding skills in Python and SQL. Expert-level knowledge of ML frameworks: TensorFlow, PyTorch, Hugging Face, scikit-learn. Practical experience with Large Language Models (LLMs), vector databases, and Retrieval-Augmented Generation (RAG) techniques.
• Cloud & Engineering: Proficient in designing solutions on Google Cloud Platform (GCP); experience with AWS or Azure is a plus. Familiarity with data tools like BigQuery, Kafka, Snowflake. Strong knowledge of MLOps, including CI/CD pipelines, model monitoring, and A/B testing frameworks.
• Governance & Ethics: Solid understanding of data privacy, governance, and responsible AI principles.