Overview

Join an amazing team that is consistently recognized for our achievements and culture, including our most recent Forbes award of being one of America's Best Midsize Employers for 2026!

Position Summary:

This position involves working on analytical projects that help identify business opportunities, answer business questions and develop business solutions. The candidate will need to have data and programming skills and be able to apply data, statistical models and machine learning techniques to understand business needs and create research and implementation plans. The candidate will also need to collaborate with cross-functional teams of software engineers, data analysts and product leaders on business initiatives.

Geo-Salary Information

An in-person interview may be required during the hiring process

State specific pay scales for this role are as follows:

$83,670 to $161,815 (NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$76,064 to $147,104 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$68,457 to $132,394 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)

In CA: Typical hiring range is $110,468 to $153,428

The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.

Responsibilities

Essential Job Functions:

The team member will work with various business departments to understand their business processes and needs.
The team member will identify and use relevant data sources to conduct project work and ad-hoc analyses using statistical and machine learning algorithms.
The team member will work independently with some guidance from senior data scientists and management.
The team member will communicate and collaborate with colleagues and managers regarding analysis needs and results.
The team member will provide data support on projects and work with business on implementation.
The team member will create and maintain monitoring procedures and reports for projects and look for ways to improve accuracy and efficiency.
Collect data from different applications and data infrastructure.
Extract, transform and load large amount of structured or unstructured data from various sources.
Apply data manipulation techniques to clean and prepare data for analysis. Review data for quality and consistency and optimize data retrieval methods when needed.
Create and maintain reports, graphs and charts through dashboard and other programming and MS Excel.
Follow procedures to streamline analysis processes.
Support automated procedures to help reduce cost and improve efficiency.
Respond to questions and requests from business on related reports.
Communicates effectively and regularly with SMEs, EBI, MTS, and Management in the various functional areas to learn about each job function.
Through this communication, the employee will be expected to expand his/her knowledge of the processes associated with these functions, and of the various KPI’s that measure business performance in each area and overall.
Creates presentations summarizing problems identified, potential solutions.
Participates in meetings with to share findings and recommendations.
Team member should have a solid background in creating and explaining relevant graphs and be proficient at preparing and presenting PowerPoint presentations.

Qualifications

Education:

Minimum:

Worker characteristics are normally acquired through the successful completion of a Bachelor’s degree in math, statistics, computer science or other related areas. Master’s Degree (or ACAS) preferred.

Experience:

Minimum:

Completion of the Summer 2026 Internship at Mercury Insurance
At least 2 years of experience in data mining and data/statistical analysis.
At least 2 years experience with SQL and statistical software packages (Python, R, SAS) required.
Experience in insurance or financial service related fields

Knowledge and Skills:

Demonstrated solid skills in data mining, machine learning, programming and optimization.
Knowledge with cloud-based advanced data and analytics environment.
Passion for problem-solving, comfort with ambiguity.
Ability to think conceptually, analytically and creatively.
Experience using R, Python and other programing languages.
Strong data skills and the ability to work with large structured and unstructured data sources.
Experience in of predictive modeling, general model building, and validation procedures.
Excellent problem-solving skil

Associate Data Scientist at Mercury Insurance