Insurance Data Scientist

Placements24; Riverton (UT); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Annual bonus

Health insurance

Retirement plan with matching

Home office stipend

Remote work flexibility

Paid time off

Job summary

Placements24 seeks an Insurance Data Scientist for a remote-first role leveraging large insurance datasets to build predictive models for risk, pricing, fraud, and customer insights. You will collaborate with actuaries, underwriters, and business stakeholders across time zones.

Ideal candidates hold a Master’s or PhD in a quantitative field, 4+ years in data science, and strong Python/R and SQL skills with ML libraries.

Qualifications

• Master's or PhD in Data Science, Statistics, CS, Mathematics or related quantitative field.
• 4+ years of experience as a Data Scientist, preferably in insurance or financial services.
• Expertise in statistical modeling, ML techniques (regression, classification, clustering, deep learning), and data mining.
• Proficiency in Python or R and libraries (scikit-learn, TensorFlow, PyTorch, pandas).
• Experience with SQL and familiarity with big data technologies (Spark, Hadoop) a plus.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently and manage remote projects.
• Knowledge of insurance products, underwriting, claims, and actuarial concepts is desirable.
• Experience with cloud platforms (AWS, Azure, GCP) is advantageous.

Responsibilities

• Develop, validate, and deploy advanced models for risk prediction, fraud detection, customer segmentation, and pricing.
• Analyze large, complex datasets to identify trends and insights for insurance operations.
• Clean and prepare data, ensuring quality and integrity.
• Design and run A/B tests and experiments to evaluate new strategies.
• Collaborate with actuaries, underwriters, claims specialists, and stakeholders to deliver actionable insights.
• Communicate findings clearly through visualizations, reports, and presentations.
• Stay updated with advances in data science, ML, and AI.
• Contribute to data infrastructure and best practices within the team.
• Automate data processes and model deployment where possible.
• Explore new data sources and techniques for business improvement.

Skills

Statistical modeling

Machine learning

Python

SQL

Data mining

Communication

Education

Master's degree or PhD in a quantitative field

Tools

scikit-learn

TensorFlow

PyTorch

pandas

Spark

Hadoop

Job description

About the Role

Our client, a cutting-edge insurance firm, is seeking a talented and analytical Insurance Data Scientist to join their fully remote team. This role is crucial for leveraging vast datasets to extract actionable insights, build predictive models, and drive data-informed decision-making across the organization. You will work on challenging projects related to risk assessment, customer behavior analysis, fraud detection, pricing optimization, and operational efficiency. The ideal candidate possesses a strong background in statistics, machine learning, and data mining, coupled with a deep understanding of the insurance industry. This is a remote-first position, requiring self-motivation, exceptional problem-solving skills, and the ability to collaborate effectively with virtual teams located across different time zones. You will be instrumental in advancing the company's data analytics capabilities and uncovering innovative solutions to complex business problems. We are looking for individuals who are passionate about data, possess a strong quantitative aptitude, and are adept at communicating technical findings to both technical and non-technical stakeholders. The successful candidate will have the opportunity to work with state-of-the-art tools and technologies to make a significant impact.

Key Responsibilities

• Develop, validate, and deploy advanced statistical models and machine learning algorithms for applications such as risk prediction, fraud detection, customer segmentation, and pricing.
• Analyze large and complex datasets from various sources to identify trends, patterns, and insights relevant to insurance operations.
• Clean, transform, and prepare data for analysis, ensuring data quality and integrity.
• Design and implement A/B tests and other experiments to evaluate the effectiveness of new strategies or models.
• Collaborate with actuaries, underwriters, claims specialists, and business stakeholders to understand their data needs and deliver actionable insights.
• Communicate findings, methodologies, and recommendations clearly through visualizations, reports, and presentations.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Contribute to the development of data infrastructure and best practices within the data science team.
• Automate data processes and model deployment where possible.
• Explore new data sources and analytical techniques to uncover novel opportunities for business improvement.

Requirements

• A Master's degree or PhD in Data Science, Statistics, Computer Science, Mathematics, Actuarial Science, or a related quantitative field.
• A minimum of 4 years of experience as a Data Scientist, preferably within the insurance or financial services industry.
• Proven expertise in statistical modeling, machine learning techniques (e.g., regression, classification, clustering, deep learning), and data mining.
• Proficiency in programming languages commonly used in data science, such as Python or R, and associated libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Experience with SQL for data extraction and manipulation, and familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication and visualization skills, with the ability to explain complex results to diverse audiences.
• Proven ability to work independently and manage projects effectively in a remote setting.
• Knowledge of insurance products, underwriting, claims, and actuarial concepts is highly desirable.
• Experience with cloud platforms (AWS, Azure, GCP) for data science workloads is an advantage.

Benefits

• Highly competitive salary and substantial annual bonus.
• Comprehensive health, dental, and vision insurance coverage.
• Generous retirement savings plan with employer matching.
• Significant home office stipend and technology allowance.
• Flexible remote working hours and the ability to work from anywhere in South Africa . Generous paid time off and company holidays.
• Opportunities for professional development, conference attendance, and further certifications.
• Access to cutting-edge data science tools and platforms.
• A collaborative and intellectually stimulating remote work environment.
• Employee Assistance Program for well-being support.