Data Scientist

Responsibilities

Build, test, deploy, and monitor AI/ML and generative AI models, coordinating closely with data scientists and ML engineers to ensure model efficacy, compliance, and system performance. Translate modeling results into actionable business insights, communicate with stakeholders, and contribute to modeling best practices and projects that improve customer satisfaction, growth, retention, and profitability.

Requirements

Requires a master’s degree in a specified quantitative or technical field and experience building and deploying statistical or machine learning models. Candidates need proficiency in a statistical programming language such as R, Python, or SAS, SQL knowledge, data preparation skills, and familiarity with model validation, CI/CD, MLflow, Git, and agile tools; experience thresholds vary by role and industry.

Skills

• Machine Learning
• Generative AI
• Predictive Modeling
• Statistical Modeling
• Python
• R
• SAS
• SQL
• Data Wrangling
• Data Quality Evaluation
• Model Testing and Validation
• Model Deployment
• CI/CD Pipelines
• MLflow
• Git
• Azure DevOps

Benefits

• Health Insurance
• Prescription Drug Coverage
• Vision Insurance
• Dental Insurance
• Short-Term Disability
• Long-Term Disability
• Supplemental Life Insurance
• Accidental Death and Dismemberment Insurance
• Voluntary Accident, Critical Illness, and Hospital Indemnity Plans
• 401(k) With Employer Match
• Company-Funded Retirement Savings Plan
• Paid Time Off
• Yearly Bonus Eligibility
• Health and Wellness Programs
• Hybrid Work Environment
• Subsidized On-Site Cafeteria
• Complimentary Workout Facility
• On-Site Wellness Center
• Adoption and Infertility Financial Assistance
• Family Care Leave
• Tuition Assistance
• Free Parking
• Corporate Matching Gifts
• Paid Volunteer Time

About this role

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

 
 
We are proud to offer our employees, their domestic partners, and their children, a wide range of insurance benefits:

Two options for your health insurance plan (PPO or High Deductible)
Prescription drug coverage (included in your health insurance plan)
Vision and dental insurance plans
Short and Long Term Disability coverage
Supplemental Life and AD&D plans that you can purchase for yourself and dependents (includes spouse/domestic partner and children)
Voluntary Benefit plans that supplement your health and life insurance plans (Accident, Critical Illness and Hospital Indemnity)

 
In addition to the above insurance offerings, our employees also enjoy:
 

A robust 401k plan with up to a 5% employer match
A retirement savings plan that is 100% company funded
Paid time off that begins with 24 days each year, with more days added when you celebrate milestone service anniversaries
Eligibility to receive a yearly bonus as a Munich Re employee
A variety of health and wellness programs provided ...

About Munich Re

Insurance · 1,001-5,000 employees · headquartered in Hartford, CT · founded 1866