Remote Insurance Data Scientist — ML for Pricing & Fraud

Placements24; Roanoke (VA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Flexible hours

Fully remote work

Health insurance

Retirement plan

Professional development budget

Job summary

Placements24 seeks a highly skilled Remote Insurance Data Scientist to join its advanced analytics team. This fully remote role focuses on leveraging vast datasets to derive actionable insights, improve predictive models, and drive strategic decisions across insurance functions.

You will develop models for pricing, fraud detection, and customer behavior, analyze large data, and collaborate with underwriting, claims, marketing, and IT to deploy data-driven solutions.

Qualifications

• Master's or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, or related.
• Minimum of 5 years as a Data Scientist with a focus on insurance.
• Proficiency in Python or R and libraries for data manipulation and ML.
• Strong SQL and big data platform experience (e.g., Spark).

Responsibilities

• Develop, implement, and refine ML models for pricing, fraud detection, and behavior prediction.
• Analyze large datasets to identify trends and actionable insurance insights.
• Collaborate with underwriting, claims, marketing, and IT to deploy data-driven solutions.
• Design and run A/B tests to evaluate model impacts and strategies.
• Communicate findings clearly to technical and non-technical stakeholders.
• Stay updated on advances in data science and AI in insurance.

Skills

Communication

Teamwork

Education

Master's or Ph.D. in a quantitative field (Data Science, Stats, CS)

Tools

Python

R

SQL

Spark

Job description

Placements24 seeks a highly skilled Remote Insurance Data Scientist to join its advanced analytics team. This fully remote role focuses on leveraging vast datasets to derive actionable insights, improve predictive models, and drive strategic decisions across insurance functions.

You will develop models for pricing, fraud detection, and customer behavior, analyze large data, and collaborate with underwriting, claims, marketing, and IT to deploy data-driven solutions.