In-Office Data Science Intern: Predictive Analytics & Insurance

plymouthrock; Boston (MA); On-site; USD 41,000 - 48,000; Full time

Benefits offered by this job

Free On-site gym access

Free Coffee and Snacks

Company social events

Lunch and Learn Leadership program

Business Casual (Can wear jeans andSne

Job summary

Plymouth Rock, a leading U.S. insurer, seeks a Data Science Intern/Co-op for a Fall start in January 2027 in Boston, MA.

The role focuses on developing predictive models for pricing, underwriting, and product strategy under a fast-paced product management framework. Responsibilities include data analysis, modeling, and implementation with emphasis on Bayesian approaches, econometrics, and communicating results to both technical and non-technical audiences.

Qualifications

• Graduate student from a program (doctoral preferred) in economics, statistics, or related field.
• Practical experience in Econometrics and Statistics, preferably in a business context.
• Strong written and oral communication skills; ability to convey technical concepts to varied audiences.
• High standards for work products and analytical rigor.
• Creative thinker able to synthesize information for business problems.
• Flexibility and resiliency characteristics of a professional.
• Knowledge of insurance tech is a plus.

Responsibilities

• Analyze internal and external data to identify drivers of expected losses and customer lifetime value.
• Develop and enhance models within Plymouth Rock's product management structure.
• Work with product teams to implement models within regulatory and competitive contexts; ensure understanding and validation.

Skills

Econometrics

Statistics

Bayesian statistics

Communication skills

Modeling

Education

Graduate student (doctoral preferred)

Tools

SQL

R

SAS

Python

Job description

Plymouth Rock, a leading U.S. insurer, seeks a Data Science Intern/Co-op for a Fall start in January 2027 in Boston, MA.

The role focuses on developing predictive models for pricing, underwriting, and product strategy under a fast-paced product management framework. Responsibilities include data analysis, modeling, and implementation with emphasis on Bayesian approaches, econometrics, and communicating results to both technical and non-technical audiences.