Senior Insurance Data Scientist

Placements24; Randburg; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Remote work

Flexible hours

Medical insurance

Professional development budget

Job summary

Placements24 is seeking a Senior Insurance Data Scientist to lead advanced analytics initiatives for our client. The role is fully remote, offering flexible hours while shaping data-driven decisions across pricing, risk, fraud detection, and customer insights.

You will work with large datasets, build predictive models, mentor junior data scientists, and translate complex results into actionable business recommendations for stakeholders.

Qualifications

• Master's or Ph.D. in a quantitative field (Data Science, Statistics, Computer Science, or related).
• 5+ years of experience in data science, with substantial insurance industry focus.
• Proficiency in Python or R and experience with ML libraries (scikit-learn, TensorFlow, PyTorch).
• Proficiency in SQL and handling large databases/data warehousing concepts.
• Strong statistical modeling, predictive analytics, and communication skills.

Responsibilities

• Design, develop, and deploy statistical and ML models for insurance applications (pricing, fraud detection, segmentation).
• Clean, transform, and analyze large datasets using advanced techniques.
• Interpret model results and translate findings into actionable business recommendations.
• Collaborate with business units to identify data-driven opportunities.
• Mentor junior data scientists and contribute to data science strategy.
• Stay current with advancements in data science, ML, and AI.

Skills

Python

SQL

R

Statistical Modeling

Education

Master's or PhD in Data Science/Statistics/CS

Tools

scikit-learn

TensorFlow

PyTorch

Job description

About the Role

Our client is looking for a highly skilled and experienced Senior Insurance Data Scientist to lead advanced analytics initiatives. This role is fully remote, offering flexibility to work from anywhere while contributing to strategic decision-making within the insurance sector. You will leverage large datasets to develop predictive models, identify key trends, and extract actionable insights to drive business growth, optimize operations, and enhance risk management strategies. This position is ideal for a data science expert with a passion for applying cutting-edge techniques to complex insurance challenges, contributing to the company's data-driven culture.

Key Responsibilities

• Design, develop, and deploy sophisticated statistical and machine learning models for insurance applications (e.g., pricing, fraud detection, customer segmentation).
• Clean, transform, and analyze large, complex datasets using advanced data science techniques and tools.
• Interpret model results and translate complex findings into clear, actionable business recommendations for stakeholders.
• Collaborate with business units to understand their challenges and identify opportunities for data-driven solutions.
• Mentor junior data scientists and contribute to the overall data science strategy and best practices.
• Stay current with the latest advancements in data science, machine learning, and AI.

Requirements

• Master's or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, or a related discipline.
• 5+ years of experience in data science, with a significant focus on the insurance industry.
• Expertise in programming languages such as Python or R, and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Proficiency in SQL and experience working with large databases and data warehousing concepts.
• Strong understanding of statistical modeling, predictive analytics, and machine learning algorithms.
• Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.

Benefits

• Highly competitive salary and performance-based bonuses.
• Fully remote work environment with flexible working hours.
• Comprehensive medical, dental, and vision insurance.
• Significant budget for professional development, conferences, and training.
• Opportunity to work on challenging and impactful projects in a data-centric organization.