Actuarial Intern

Internship On Site (Internship) @Milliman in Actuarial
  • New Delhi View on Map
  • Post Date : February 16, 2022
  • Apply Before : March 18, 2022

Job Description

The Life & Annuity Predictive Analytics (LAPA) business unit is a lean, agile, diverse, and geographically distributed data science startup within Milliman. We develop leading edge data products and deploy them on the cloud as web applications for the world’s premiere life insurers.

As an Actuarial Intern on the LAPA team, you will play a key role in the development, testing, deployment, and maintenance of data processing and analytics infrastructure that prepares data for predictive modeling. You will work closely with other data scientists, data engineers, software engineers, and domain experts to continuously improve our data collection, data cleaning, data analysis, predictive modeling, data visualization, and reporting pipeline.

Primary Responsibilities:

  • Perform initial explorations and datachecks on data (Python and SQL)
  • Develop data preparation and data analysis scripts (Python and SQL)
  • Support development of internal processes to validate and visualize raw and prepared data
  • Document and communicate data analysis results

Required knowledge and experience:

  • Basic actuarial domain knowledge of life and annuity products
  • Passed one or more actuarial exams
  • Proficiency developing scripts for data manipulation (Python required)
  • Knowledge of SQL and data retrieval
  • Passion for data, computing, and problem solving
  • Ability to work in a highly collaborative environment as well as independently with minimum supervision
  • Ability to take ownership of a technical challenge and see it through to a successful conclusion
  • Excellent written and verbal communication skills

Preferred knowledge and experience:

  • Experience with distributed computing technologies (Databricks, Spark, H2O, Hadoop, etc.)
  • Advanced programming skills in Python including pandas and NumPy
  • Advanced programming skills in R including experience with the tidyverse suite of packages
  • Experience with RStudio Shiny web application framework
  • Basic knowledge of web application technology (JavaScript, HTML, and CSS)

Required education:

  • Bachelors in a quantitative field/Bachelors of science (e.g. Computer Science, Actuarial Science, Engineering, Statistics/Mathematics, Data Science, etc.)
    • Final year students are eligible to apply for this position
  • Pursuing Actuarial science qualification from any recognized institute

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