Insurance Data Science Consultant

Earnix•Boston, MA

2d•$78,000 - $142,000

About The Position

Earnix is seeking a Professional Services Consultant with a strong analytics background in the insurance industry, ideally holding an ACAS or near-ACAS designation. The consultant supports clients in using Earnix software for data extraction and analysis, develops and reviews statistical models, and helps implement effective pricing strategies. The role develops and maintains predictive models to assess risk and customer demand, applying machine learning and programming languages such as Python and R. It also involves communicating technical results to varied audiences, demonstrating software functionality, and training new users to support onboarding. Earnix provides cloud-based intelligent decisioning solutions for pricing, rating, underwriting, and product personalization to insurers and banks. The company has served customers in over 35 countries since 2001 and has offices across the Americas, Europe, Asia Pacific, and Israel.

Requirements

Extensive experience in the insurance industry, specifically in analytics and predictive modeling.
Proficiency in machine learning methods and programming languages such as Python and R.
Exceptional communication skills and the ability to present technical information accessibly.
Strong ability to engage clients and provide valuable insights through data analysis.

Nice To Haves

ACAS or near-ACAS designation.
Focus on the art of the possible.
Communicate with honesty, candour, and respect.
Collaborate seamlessly with colleagues across the company.
Be resourceful and creative.
Act with empathy.

Responsibilities

Develop and maintain predictive models to assess risk and customer demand and guide pricing strategies across lines of business.
Use machine learning techniques and programming languages such as Python and R to enhance analytics capabilities.
Communicate complex technical results clearly and tailor presentations for diverse audiences.
Demonstrate software functionality and train new users to support onboarding.
Support clients’ use of the software for data extraction and analysis.
Develop and review statistical models and help implement pricing strategies.
Engage clients and provide insights through data analysis.