Telematics Data Scientist - Business Data & Analytics

We are seeking a Telematics Data Scientist to build foundational analytics that connect claims and telematics data, uncover actionable driver-level insights, enable AI- and automation-driven capabilities, support IoT data discovery, and lay the groundwork for future telematics-enabled decision making.

The ideal candidate combines curiosity, data engineering, data science, and analytical skills with disciplined documentation and a product-minded approach, ensuring assets are reusable, scalable, and aligned to enterprise expectations.

Great American's culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are expected to be onsite four days a week, with the flexibility to work one day remotely. Core in-office days are Tuesday-Thursday, with the fourth day determined by business needs.

Essential Job Functions & Responsibilities

• Develop and iterate claims-to-telematics join logic, contributing analytical, data engineering, and documentation capacity to expand the share of claims successfully linked to telematics data.
• Build reusable analytical components that support future pricing enablement, including exploratory and production-ready logic for fleet behavior monitoring, trend-shift detection, and trip- and geography-based risk signals.
• Identify opportunities where telematics-derived analytics can be embedded into AI- or automation-driven workflows.
• Design and optimize Snowflake data structures (tables, schemas, and queries) to provide high-quality, scalable foundations for downstream modeling, reporting, and automation.
• Document analytical logic, data structures, and decision rationale to support long-term maintainability, auditability, and knowledge transfer.
• Improve schema design, reduce duplication, standardize table usage, and support onboarding of new telematics or IoT-derived data sources.

• Bachelor's in Data Science, Computer Science, Business Analytics, Neuroscience, or related fields. Master's degree in these fields would be highly preferred.
• 3 or more years of related experience.
• Strong SQL proficiency.
• Experience with unsupervised machine learning techniques to surface patterns, hypotheses, and emerging risk signals.
• Experience with hypothesis-driven modeling with domain-informed features and constraints.
• Hands-on experience with Python for data transformation, feature engineering, and building data pipelines that support machine learning workflows and automation.
• Strong documentation habits, with the ability to clearly explain analytical logic, data structures, and decisions.

Preferred Skills

• Practical experience with Snowflake data modeling, including table and schema design and query performance optimization.
• Experience with geospatial or grid-based analytics (e.g., H3 or similar).
• Background in insurance, fleet, risk, or pricing analytics, particularly where telematics or sensor data is involved.

We offer competitive benefits packages for full-time and part-time employees*. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.

Be Here. Be Great. Working for a leader in the insurance industry means opportunity for you. Great American Insurance Group's member companies are subsidiaries of American Financial Group. We combine a "small company" culture where your ideas will be heard with "big company" expertise to help you succeed. With over 30 specialty and property and casualty operations, there are always opportunities here to learn and grow. At Great American, we value and recognize the benefits derived when people with different backgrounds and experiences work together to achieve business results. Our goal is to create a workplace where all employees feel included, empowered, and enabled to perform at their best.