Job Description

We are also looking for a go getter person who can define:

• Has excellent hands-on experience working on end-to-end model development process using AI and ML models, preferably in Insurance 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 4+ years of experience in a similar role and should possess a go -getter attitude. He/ She should be able to deal with ambiguity.

The job responsibilities include the following:

• 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.

Required Education and Essential Skills

• Academic Background in Science (Mathematics, Physics, Engineering, Statistics, Economics, Actuarial Science etc.)
• Essential Technological skills:
  • Hands-on experience in developing and deploying Machine Learning, Generalized Linear Models and Deep Learning 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
  • Working knowledge of any cloud environment
• Experience in P&C Insurance Industry is preferable.