Provide technical direction to project team members across data modeling, data manipulation, visualization, predictive modeling, Reporting and Automation projects across Insurance Value Chain
Facilitate client working sessions and lead recurring project status meetings
Manage day-to-day project operations, serve as the functional and domain expert on the project team to ensure that they meet client expectations.
Responsibilities
Bachelor’s/master’s degree in economics, mathematics, computer science/engineering, operations research or related analytics areas; candidates with BA/BS degrees in the same fields from the top tier academic institutions are also welcome to apply
12+ years’ Core Analytics experience (Data Science, Gen-AI,Large Language Models, including prompt engineering, embeddings, Retrieval-Augmented Generation, vector databases, and model evaluation, ML-AI Model Development, Data Engineering, Databricks) with prior Consulting/Implementation Experience preferably with Life Insurance Clients.
Working knowledge of MLOps and model lifecycle practices, including model deployment support, monitoring, drift detection, retraining, and tools such as MLflow, Airflow, Docker, Kubernetes, or cloud-native ML platforms.
Experience on any cloud (AWS / Azure/ GCP), is an added advantage.
Experience working with Microsoft Fabric is a plus.
Experience in working in dual shore engagement and must have experience in managing clients directly
Complete understanding and demonstrated experience of Python, SQL, Tableau, Power BI and Could Data Storage Solutions like Snowflake/S3/ADLS Gen2 and various modeling techniques
Managerial experience in leading analytics teams including career management of offshore staff, training, recruiting.
Demonstrated leadership ability and willingness to take initiative
Strong record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work
Outstanding written and verbal communication skills
Able to work in fast pace continuously evolving environment and ready to take up uphill challenges
Can understand cross cultural differences and can work with clients across the globe
Qualifications
Bachelor’s/master’s degree in economics, mathematics, computer science/engineering, operations research or related analytics areas; candidates with BA/BS degrees in the same fields from the top tier academic institutions are also welcome to apply
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