Senior Data Scientist

Great American Insurance Group · Cincinnati

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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.

Great American Risk Solutions (GARS) is a growing wholesale excess & surplus (E&S) insurance business focused on complex and specialized commercial risks. As a dynamic and expanding business, GARS combines the entrepreneurial spirit of a growth-oriented organization with the stability and resources of Great American Insurance Group. The GARS Analytics Team develops reporting and analytics that enable better decision-making across a complex and evolving commercial portfolio. We are seeking a Senior Business Intelligence Analyst to serve as a technical leader and strategic partner driving analytics delivery, advancing our use of modern tools, and helping scale our capabilities as demand continues to grow. 

Great American’s culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are expected to be on‑site 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 and Responsibilities

Modeling and Analytics Leadership

• Applies advanced subject matter expertise to shape data science strategy and business potential for the organization. Works independently with limited supervision. Leads small to moderately complex projects from design through deployment and serves as a technical mentor to junior team members. Has a high level of understanding of the organization’s business and technology operations and a strong working knowledge of department policies and procedures.

• Leads the design, development, validation, and deployment of predictive models for underwriting, pricing, claims, and customer retention, from initial study design through production rollout.

• Analyzes large, complex, high-dimensional datasets, using structured and unstructured sources, to identify trends, patterns, risk factors, and opportunities that drive measurable business value.

• Creates models, simulations, and optimization routines, and selects the right technique for the business problem rather than the most complex one.

• Monitors and maintains the performance of models in production, including drift detection, retraining, and ongoing tracking and follow-up studies.

Data, Automation, and Engineering

• Designs and implements data pipelines, automated reporting tools, and dashboards that track key business metrics and provide actionable insights.

• Partners with data engineers to ensure data quality, accessibility, and scalability, and defines data acquisition strategies that enable the capture and sharing of data and analytics across the organization.

• Identifies opportunities to apply artificial intelligence, machine learning, and automation to replace manual work for revenue-generating teams, and leads the delivery of those solutions.

Business Partnership and Influence

• Partners with actuarial, underwriting, claims, and product teams to translate business problems and opportunities into technical requirements and data science specifications.

• Acts as a trusted advisor to business leaders, using data and analytics to shape decisions, and weighs the big picture and business impact in addition to model metrics.

• Communicates insights and recommendations to senior leadership through clear data storytelling and visualization.

• Provides input into GARS product roadmaps and takes an active role in agile planning and documentation for minimum viable products and long-term roadmaps.

Governance and Innovation

• Ensures models meet insurance regulatory requirements and internal model governance standards, including documentation, explainability, bias and fairness testing, and validation.

• Drives innovation by evaluating new data sources, modeling techniques, and technologies, and brings proven approaches into production.

• Drives accountability for value recognition and business results from data science work.

Mentorship and Culture

• Mentors and provides technical guidance to junior data scientists and analysts, including code and model reviews, and helps set team standards for modeling, coding, and documentation.

• Helps build a culture that values analytics as a business competency, including leading training sessions and advocating for the benefits of analytics across GARS.

• Performs other duties as assigned.

Qualifications

• Programming Language Skills: Expert in Python and its core machine learning libraries (e.g., scikit-learn, XGBoost, LightGBM). Experience with R is a plus.

• Database Skills: Advanced proficiency creating, retrieving, and optimizing data via SQL in Snowflake or a comparable SQL database.

• Cloud and Pipeline Skills: Experience with a major cloud platform (AWS, Azure, or GCP) and data pipeline tools (e.g., Airflow, dbt).

• Presentation Skills: Strong proficiency in data visualization and dashboard development using Tableau or Power BI, and the ability to present complex problems and solutions to senior leaders.

• Preferred: Experience with geospatial data, telematics, or catastrophe modeling.

Job Requirements

• Education: Master’s degree in data science, statistics, computer science, actuarial science, or a related quantitative field, or equivalent work experience, is required. PhD preferred.

• Experience: Generally, a minimum of 6 years of experience exploring and manipulating large datasets, leveraging structured and unstructured data sources, and applying predictive modeling, including taking models from concept to production. Proven experience in techniques for optimizing models, machine learning, and analytical programming.

Business Unit:

Benefits:

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.

Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process. Learn more at http://www.gaig.com/careers.

*Excludes seasonal employees and interns.

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