Own the end-to-end lifecycle of analytical initiatives from problem framing and data exploration to model deployment and business adoption
Lead the design and implementation of intelligent, scalable AI systems, including use cases in Generative AI (e.g., workflow automation, document intelligence) and agent-based AI (autonomous decisioning and orchestration)
Act as a bridge between business and data, collaborating with cross-functional teams including operations, product, tech, and finance.
Drive the use of advanced data science techniques (machine learning, optimization, simulation) to improve business outcomes.
Promote data governance, reproducibility, and sustainable practices in model development and deployment.
Communicate complex findings through clear narratives and visual storytelling to influence senior leadership.
Build, mentor, and manage a high-performing analytics team, fostering a culture of innovation, agility, and accountability (This is only applicable at Senior Manager level)
Core Technical Skills
Proficient in SQL, Python, and working with large, complex datasets
Strong background in ML/AI including supervised/unsupervised models, feature engineering, and model evaluation
Hands-on experience with cloud-based data & ML platforms (e.g., AWS SageMaker, GCP Vertex AI, Azure ML)
Familiarity with LLMs, vector databases, prompt engineering, and orchestration frameworks (LangChain, LangGraph, or similar)
