Sr. Data Scientist
Summary
Leads AI/ML model development and MLOps for predictive, prescriptive, and generative solutions while managing client engagements and program governance.
Core Responsibilities
Client & Program Leadership
- Serve as primary client partner for analytics engagements, shaping problem statements, defining success criteria, and managing executive updates.
- Translate business goals into data science roadmaps and measurable outcomes.
- Establish and run program governance (steering committees, RAID logs, change control, dependency management).
Delivery & Value Realization
- Own scope, plan, and delivery across multiple workstreams; track timelines, budgets, and outcomes; ensure on‑time, on‑budget delivery.
- Define value baselines and benefit tracking .
- Lead end-to-end development of AI/ML models including problem formulation, data exploration, feature engineering, model training, validation, and deployment.
- Design and implement predictive, prescriptive, and generative AI solutions using structured and unstructured data.
- Drive adoption of ML best practices, including model explainability, fairness, bias detection, and performance monitoring.
Data Science & MLOps Leadership
- Lead end-to-end development of AI/ML models including problem formulation, data exploration, feature engineering, model training, validation, and deployment.
- Design and implement predictive, prescriptive, and generative AI solutions using structured and unstructured data.
- Drive adoption of ML best practices, including model explainability, fairness, bias detection, and performance monitoring.
- Architect and oversee production-grade ML pipelines using MLOps principles.
Professional certification such as CA, CPA, CISA or CIA. 7-9 years of experience.