Lead Data Scientist
Core
Lead the design and delivery of enterprise-scale AI, machine learning, and advanced analytics solutions for global clients, combining technical leadership with hands-on data science expertise.
Role type
Lead Data Scientist (Strategy & Hands-on IC)
Builds
Scalable analytical and AI solutions, data governance frameworks, and production ML models for enterprise clients.
Domain
Enterprise Technology / Data & AI / Cloud Infrastructure
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Machine Learning (regression, classification, clustering, time series), Statistical analysis and modeling, End-to-end ML lifecycle management, SQL, AI metadata service design, Team leadership, Requirements elicitation, ETL and data curation, Agile methodologies, Model explainability, MLOps practices.
Preferred skills
Generative AI and RAG experience, Banking/Financial Services/Insurance domain knowledge, AI governance expertise, Multi-cloud platform experience, Client-facing solution design.
Technologies
GCP (Dataflow, Dataproc, BigQuery, Dataplex, Vertex AI), Azure (ADF, Synapse, AzureML, Purview), Databricks, Looker, Power BI, Python, SQL, Jira, Azure DevOps.
Responsibilities
Lead data science teams and define best practices for data science frameworks, Design and implement data services for enterprise AI requirements including governance and metadata, Translate business problems into predictive modeling and optimization solutions, Develop and deploy ML models using classification, regression, and clustering techniques, Engineer features and prepare datasets to improve model performance, Apply statistical methods and A/B testing to validate models, Design MLOps practices for model versioning and monitoring, Collaborate with data engineers to scale datasets from cloud platforms, Present insights through data visualization and storytelling.
Seniority
Senior, hands-on IC with leadership responsibilities
