About this role
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.