Senior Data Scientist, Insurance Analytics

About

Our client, a leading innovator in the insurance technology sector, is seeking a highly accomplished Senior Data Scientist to spearhead advanced analytics initiatives from a remote capacity. This is a unique opportunity to leverage cutting‑edge data science techniques to drive strategic decision‑making within the insurance domain. You will be responsible for developing sophisticated predictive models, identifying key risk factors, optimizing pricing strategies, and enhancing customer segmentation. The ideal candidate possesses a strong background in statistical modeling, machine learning, and data mining, coupled with a deep understanding of the insurance industry's complexities. This role requires exceptional analytical prowess, programming skills, and the ability to translate complex findings into actionable business insights.

Key Responsibilities

• Design, develop, and implement advanced statistical and machine learning models for risk assessment, fraud detection, and customer lifetime value prediction.
• Analyze large, complex datasets from various sources to uncover trends, patterns, and actionable insights relevant to the insurance business.
• Collaborate with product, underwriting, and marketing teams to define analytical requirements and deliver data‑driven solutions.
• Develop and maintain robust data pipelines and analytical frameworks for continuous model evaluation and improvement.
• Utilize programming languages such as Python or R, and libraries like scikit‑learn, TensorFlow, or PyTorch for model development.
• Explore and experiment with new algorithms and technologies to stay at the forefront of data science.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non‑technical stakeholders through presentations and reports.
• Mentor junior data scientists and contribute to the growth of the data science practice within the organization.
• Ensure data quality, integrity, and ethical considerations are maintained throughout the analytical process.
• Contribute to the development of data strategy and roadmap for the insurance analytics function.
• Monitor the performance of deployed models and implement necessary adjustments or retraining.
• Work remotely, ensuring proactive communication and collaboration with global teams.

Qualifications

• Master's degree or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, Mathematics, Physics, or a related discipline.
• Minimum of 6 years of professional experience in data science, with a significant focus on applying machine learning and statistical modeling to real‑world problems.
• Demonstrated experience within the insurance industry or financial services sector, with a solid understanding of insurance products, actuarial principles, and risk management.
• Expert proficiency in Python or R, including extensive experience with data manipulation, analysis, and machine learning libraries (e.g., Pandas, NumPy, SciPy, scikit‑learn, Keras, TensorFlow).
• Strong experience with SQL for data extraction and manipulation from relational databases.
• Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent understanding of various machine learning algorithms, including regression, classification, clustering, time series analysis, and deep learning.
• Proven ability to work independently, manage projects, and deliver results in a remote setting.
• Strong problem‑solving skills and a rigorous, analytical mindset.
• Excellent written and verbal communication skills, with the ability to present technical concepts to diverse audiences.

Benefits

• Competitive salary
• Comprehensive benefits
• Opportunity to shape the future of insurance analytics
• Remote work