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Senior, specialized Gen-AI and insurance consulting requirements create moderate competition.
Prefers insurance consulting experience and deep ML/MLOps expertise, limiting cross-industry transferability.
Explicit 12+ years plus many mandatory ML, MLOps, and insurance domain requirements.
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Provide technical direction across data science projects involving data modeling, predictive modeling, visualization, reporting, and automation within the insurance value chain.
Lead client working sessions and manage recurring project status meetings ensuring client expectations are met.
Manage day-to-day project operations and serve as functional and domain expert, including leading and developing offshore analytics teams.
12+ years of core analytics experience including Data Science, Gen-AI, Large Language Models, ML-AI Model Development, Data Engineering, and Databricks.
Bachelor’s or master’s degree in economics, mathematics, computer science/engineering, operations research, or related analytics fields (top tier institutions also acceptable).
Proven consulting or implementation experience preferably with life insurance clients.
Working knowledge of MLOps/model lifecycle tools (MLflow, Airflow, Docker, Kubernetes), and proficiency in Python, SQL, Tableau, Power BI, and cloud data storage solutions like Snowflake/S3/ADLS Gen2.
Experienced leader with managerial experience managing and developing analytics teams, including offshore staff.
Strong expertise implementing advanced data science solutions and Gen-AI technologies within insurance or related domains.
Effective client-facing skills with ability to work in dual shore engagements and manage clients directly, comfortable in fast-paced, evolving global environments.