Engagement Manager Data Science

• 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