Engagement Manager (Data Science)
Posted Updated 3
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Summary
Lead data-science projects for insurance clients, guiding teams on modeling, automation, and Gen-AI solutions while managing client relationships and project delivery.
- 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.
- 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
- 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
Skills
- AI
- Airflow
- Analytics
- Automation
- AWS
- Azure
- Cloud
- Cloud Native
- Data Engineering
- Data Modeling
- Data Science
- Databricks
- Docker
- Embeddings
- GCP
- Generative AI
- Kubernetes
- LLM
- Machine Learning
- Microsoft Fabric
- MLflow
- MLOps
- Model Deployment
- Model Evaluation
- Power BI
- Predictive Modeling
- Prompt Engineering
- Python
- RAG
- S3
- Snowflake
- SQL
- Tableau
- Vector Databases