Data Scientist

Data Scientist

Drive the future of AI-powered decision-making by leading sophisticated machine learning and GenAI solutions that shape strategy and outcomes.

American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers products and services for residential property – such as manufactured homes and specialty dwellings – and the recreational market, including boats, personal watercraft, classic cars, and more. We provide specialty product solutions that cover what the competition often can't. We write admitted products in all 50 states and have a premium volume of $2.2 billion.

Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of Munich Re's Global Specialty Insurance division. Our employees receive boundless opportunity to grow their careers and make a difference every day - all in a flexible environment that helps them succeed both at work and at home.

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on developing and maintaining predictive models that support all domains across the business. In this role, you'll collaborate closely with senior data scientists to build and support AI/ML and Gen AI models. You will test models to ensure efficacy and compliance before deployment, work hand-in-hand with ML Engineers to deploy models and verify system performance, and monitor models post-deployment, making adjustments as needed. Join us in building AI/ML models that truly drive business value and make a measurable impact.

Roles & Responsibilities:

• Build and deploy AI/ML models with general guidance.
• Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing.
• Participate in the development of modeling presentations and present results/topics to stakeholders (internal & external) and management as requested.
• Concentrate on loosely defined problems which require application of creative approaches. Contribute to projects that yield actionable insights the business can use to increase customer satisfaction, policy growth, retention, and profitability.
• Complete required data preparation, including data input with guidance. Identify data anomalies and seek guidance on necessary adjustments.
• Identify data and operational issues requiring specialized analytics attention, data scrubbing, and modeling techniques.
• Document and communicate assumptions, results, and alternatives to team members and internal stakeholders with guidance.
• Create and maintain modeling best practices and new techniques in coordination with internal and external business partners.
• Explain advanced analytic and modeling procedures in the language that audiences with no predictive analytics training can easily find connections to. Understand stakeholders' requests and hidden issues and explain possible solutions in their language.
• Schedule and prioritize workload demands. Maintain very good organization skills. Complete technical peer reviews as needed.
• Maintain strong interpersonal skills - listen deeply, ask correct questions, take notes, complete professional oral and written business communications (including email communications), presentations, and build business relationships in order to better understand insurance company processes and functions. Established relationships with multiple areas of interaction.

Required Technical Skills:

• Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside general programming and SQL knowledge.
• Demonstrated experience building and deploying statistical and machine learning models to address business challenges.
• Skilled in data wrangling, quality evaluation, transformation, and cleaning for analysis.
• Experience with AI/ML model testing, validation, deployment, and integration into CI/CD pipelines.
• Familiarity with tools such as MLflow for model experimentation and registration, Git for version control, and agile frameworks using tools like Azure DevOps.

Skills / Knowledge / Experience:

• Develop and project manage modeling projects and statistical analyses.
• Effectively communicate results to business partners and help drive business decisions.
• Participate in creation and discussion of best practices and propose new techniques.
• Mentor junior team members.
• Data Scientist: 2 or more years of data science/predictive analytics experience in (re)insurance or 4 or more years predictive modeling experience in another industry.
• Sr. Data Scientist: 4 or more years of data science/predictive analytics experience in (re)insurance or 6 or more years predictive modeling experience in another industry.

Education, Certifications & Designations:

• Master's degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science double major or Statistics/Math and Operation Research double major