Remote Insurance Data Scientist

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

About the Role

Our client is seeking a highly skilled and innovative Remote Insurance Data Scientist to join their advanced analytics team. This fully remote position is critical for leveraging vast amounts of data to derive actionable insights, enhance predictive modeling, and drive strategic business decisions across all insurance functions. You will work with cutting-edge technologies to tackle complex challenges in areas such as fraud detection, risk assessment, customer segmentation, and operational efficiency. This role offers an exceptional opportunity for a data-driven individual to shape the future of insurance through advanced analytics from the comfort of their home office.

Key Responsibilities

• Develop, implement, and refine machine learning models for pricing, fraud detection, and customer behavior prediction.
• Analyze large, complex datasets to identify trends, patterns, and actionable insights relevant to the insurance business.
• Collaborate with underwriting, claims, marketing, and IT teams to integrate data-driven solutions.
• Design and conduct A/B tests and experiments to evaluate the impact of new models and strategies.
• Communicate complex findings and recommendations clearly to both technical and non-technical stakeholders.
• Stay current with the latest advancements in data science, machine learning, and AI within the insurance domain.

Requirements

• Master's or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, or a related discipline.
• Minimum of 5 years of experience as a Data Scientist , with a significant focus on the insurance industry .
• Proficiency in programming languages like Python or R, and expertise in libraries for data manipulation and machine learning (e.g., Pandas, Scikit-learn, TensorFlow).
• Strong experience with SQL, database technologies, and big data platforms (e.g., Spark).
• Proven ability to translate business problems into data science solutions and deliver measurable results.
• Excellent communication and collaboration skills, essential for a remote team environment.

Benefits

• Highly competitive remote salary and substantial performance-based bonuses.
• Fully remote work arrangement with flexible working hours.
• Comprehensive health, dental, and vision insurance plans.
• Generous contribution to a retirement savings plan.
• Access to state-of-the-art tools and platforms, plus a dedicated budget for professional development and training.