Hiring for Lead Data Science

2 weeks ago

Gurugram Haryana India, IN EXL Full time

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 – Handle 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.
  • Participate in various other analytics projects and work on ad-hoc requests relating to data extractions and visualizations as per the client need

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


  • Analytic strategies to meet the demands of business requirements
  • Technical requirements of the analytic solutions
  • Data requirements of the analytic solution processes
  • 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 suitable candidate should have 8-12 years of experience in a similar role and should possess a go -getter attitude. He/ She should be able to deal with ambiguity
  • Experience in insurance preferred but not mandatory.


Personal Qualifications

  • Deep understanding of Analytics
  • Strong communicator and team player. Should have experience in client interactions.


Required Education and Skills

  • Academic Background in Science (Mathematics, Physics, Engineering, Statistics, Economics, Actuarial Science etc.)
  • Strong IT skills - Hands on experience in Machine Learning, Data Analysis and Data Preparation tools like Python, Pyspark, SQL, and good knowledge in advanced analytics / Machine learning / statistical / data mining / Text mining techniques in Regression or classification

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