Job details
Description
The Department

The Life & Annuity Predictive Analytics (LAPA) business unit is a lean, agile, diverse, and geographically distributed data science startup within Milliman. Our team consists of professionals with varied backgrounds including data scientists, data engineers, software engineers/developers, and actuarial domain experts.

We help insurers and distributors of life and retirement products to understand and use their own data, industry data, and customer data to advance their competitive position and improve financial outcomes. Through our powerful combination of subject matter expertise, data management, and advanced analytics, we provide our clients with tools to analyze their business performance, manage risk, and generate new business leads to facilitate more profitable growth.

 

The Role

 

This role will primarily be responsible for 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.

 

You will:

Develop data preparation and data analysis scripts (Python and SQL)
Take ownership of the inputs/outputs for a data preparation pipeline
Support development of internal processes to validate and visualize raw and prepared data
Document and communicate data analysis results
 

Job Knowledge, Experience Skills

 

Job Knowledge Required

Bachelors in a quantitative field/Bachelor of Science (e.g., Computer Science, Actuarial Science, Engineering, Statistics/Mathematics, Data Science, etc.)
0 – 2 years of professional work experience in a data analyst or technical actuarial role.
Freshers and final year students are eligible to apply for this position.
Pursuing Actuarial science qualification from any recognized institute (e.g., IFoA, IAI, SOA)
Experience with common data analysis tools (e.g., Python, R, SQL)
 

Experience and Soft Skills Required

Basic actuarial domain knowledge of life and annuity products
Passed one or more actuarial exams
Proficiency developing scripts for data manipulation (Python required)
Experience with SQL and data retrieval
Passion for data, computing, and problem solving
Ability to work in a fast-paced environment where the client is always our first priority
Proven record of reliability and dedication to high quality work
Sharp critical thinking skills, sound judgment, and decision making ability
Both the ability and willingness to clearly articulate your ideas.
Strong written and verbal communication skills
Ability to work both collaboratively and independently
 

Additional Knowledge and Skills to Build

Demonstrated aptitude for quantitative and critical thought
Experience working with cloud-based computing platform (e.g., Databricks)
Advanced analytical programming using spark-based languages (PySpark, SparkSQL)
Familiarity with fundamentals of predictive modeling and other statistical methods
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