Lead Data Scientist

Job description

Machine Learning & Data Science Lead the design, development, and deployment of advanced Machine Learning solutions to solve complex business and operational challenges. Develop and optimize models across areas such as classification, clustering, anomaly detection, forecasting, recommendation systems, and predictive analytics. Drive the full model lifecycle from data exploration and feature engineering through experimentation, evaluation, deployment, and monitoring.

Define model performance metrics, validation frameworks, and success criteria to ensure business relevance and measurable impact. Identify opportunities to leverage data and AI to improve operational efficiency, automation, decision-making, and user experience. Guide best practices in statistical analysis, experimentation, model governance, and AI quality assurance. Mentor and provide technical leadership to Data Scientists and AI practitioners across the organization.

Generative AI & Agentic AI Lead the design and implementation of Generative AI solutions leveraging Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and multi-agent architectures. Develop AI agents capable of reasoning, planning, knowledge retrieval, and task orchestration within complex enterprise environments. Evaluate emerging AI technologies, models, and frameworks to identify opportunities for innovation and business value creation.

Design and optimize prompt engineering, evaluation methodologies, guardrails, and AI safety mechanisms. Define architectures for agentic systems integrating enterprise data, business workflows, APIs, and knowledge repositories. Establish evaluation frameworks to measure accuracy, reliability, explainability, and operational readiness of GenAI and Agentic AI solutions. Drive proof-of-concepts and pilot initiatives from ideation through industrialization and production adoption.