Sibling is seeking an accomplished Data Scientist to join a high-performing team within a world-class insurance provider headquartered in Raleigh, North Carolina. In this role, you will leverage advanced analytics, including statistical modelling, machine learning, and predictive analysis, to deliver data-driven solutions that influence critical business decisions and mitigate risk. You will collaborate with senior leaders, drive strategic initiatives, and play a key role in shaping innovative approaches across the organization. This is an exciting opportunity to elevate your career by transforming complex data into actionable insights that drive measurable business results.
Key Tasks:
Conduct sophisticated data analysis on structured and unstructured data sets, utilizing advanced techniques such as data mining, inferential statistics, and predictive modelling to generate actionable business insights.
Lead and support strategic initiatives by owning solution design, technical delivery, and business outcome measurement.
Extract, interpret, and present data from multiple sources, resolving data discrepancies and customizing key findings for diverse executive and business audiences.
Provide analytical consulting and thought leadership to business leaders and partners, fostering strong relationships and helping integrate data-driven decision-making across the enterprise.
Co-design scalable and reusable solutions that address complex business challenges, following best-in-class coding standards, clear documentation practices, and a commitment to long-term business value.
Exercise sound judgment in risk management
Qualifications:
Bachelor's Degree.
5+ Years experience in Data Science, Ideally in insurance/financial services
Demonstrated subject matter expertise in financial services, fintech, quantitative risk management, or financial regulation, evidenced by a strong career trajectory.
Advanced knowledge of statistics, programming (Python, R, SAS), machine learning, model development, and data visualization.
Strong command of big data technologies, including Hadoop, Pig, Hive, Spark, and NoSQL databases.