Senior Data Scientist

This position is for a Senior Data Scientist in the P&C Insurance AI and ML model development domain for one of our clients. The key responsibility will be to support the client's Insurance Analytics team in undertaking various Analytics, AI and Data Science projects.

• Academic Background in Science (Mathematics, Physics, Engineering, Statistics, Economics, Actuarial Science etc.)
• Essential Technological skills:
  • Hands-on experience in developing and deploying Machine Learning and Generalized Lineal Models as well as data preparation, transformation and analysis
  • Well versed in model development, validation, and monitoring process
  • Expertise in tools like Python, Pyspark, SQL
  • Good knowledge of Natural Language Processing and Text Mining
  • Working knowledge with AWS Services like S3, EC2, EMR, Airflow, Sagemaker
  • Working knowledge of Snowflake
• Experience in P&C Insurance Industry is preferable.
• Has excellent hands-on experience working on end-to-end model development process using AI and ML models, preferably in Financial Services domain
• Has worked on defining, developing and deploying ML/AI projects
• Has developed analytical strategies to meet the demands of business requirements and convert business problems into data science-based solutions 
• The person will be part of the Data Science team for a major Insurance client. He/ She will work with different stakeholders as SME for data science.
• Engages in technical problem solving across multiple technologies; often needs to develop new solutions.
• A typical workday will involve collaborating with stakeholders as an individual contributor or with junior data scientists to gather requirements, develop AI/ML models and deploy them to achieve business objectives.
• A suitable candidate should have 7-10 years of experience in a similar role and should possess a go -getter attitude. He/ She should be able to deal with ambiguity.
• Deep understanding of Analytics and Data Science and how it can be integrated into business process
• Strong communicator, Problem Solver and team player. Should have experience in client interactions both technical and non-technical
• Experience of working in a multi-cultural environment

• Clearly Setting Project Objectives with the Client – Take initiatives to identify opportunities and develop problem statements to be worked upon. 
• Data Extraction, Cleansing and Manipulation – Manage large volume of data, research for variables and work with structured/unstructured data. 
• Predictive Modelling – Development of models using appropriate predictive analytics techniques.
• Model Documentation – Clear and Detailed Documentation of the modelling procedures.
• Model Deployment and Automation
• Participate in various other analytics projects and work on ad-hoc requests relating to data extractions and visualizations as per the client’s need.
• Modeling / Data Science: Model training and development, Model monitoring, refitting models, diagnostics/analysis and publishing the model.
• Model pipeline automation via airflow documentation.
• Development dashboards containing model validation and monitoring KPIs.