Benjamin Schnoor
Madison,WI
Summary
Data Scientist and Machine Learning Engineer with experience in AI integration, predictive modeling, and data engineering. At QBE Insurance, I developed strong analytical capabilities and effective communication skills through cross-functional collaboration. Known for delivering impactful solutions by combining technical expertise with a commitment to continuous learning and innovation.
Overview
2
2
years of professional experience
Work History
Machine Learning Engineer
QBE Insurance
Sun Prairie, WI
01.2024 - Current
- In a MLE team of 5 to 15 members, we used Python to deliver AI initiatives, models, and backend development for our data scientists, IT professionals, and actuaries.
- Created foundational data science and MLE tools and functions from the ground up.
- Created a PDF data extractor using OCR methods combined with OpenAI GPT-4o and Pydantic; this effectively converted PDFs to CSV files, saving precious time for internal stakeholders.
- In the backend development of models, I used tools such as Pydantic, OpenAPI, Postman, and pipelines to support the safe deployment of API endpoints used by our IT frontend team.
- Led the team in developing CI/CD pipelines to ensure best practices were followed, and model deployments functioned as expected.
- Developed a tool to analyze and visualize data drift in models.
- On-leveled previous model data to current models to check model improvements, and how to further improve the models.
- All projects were Git-backed and run in Domino Data Lab or Databricks.
- Worked in an Azure environment, utilizing Jira to organize tasks.
- Gained entry-level knowledge in Terraform and resource provisioning through Azure.
- Developed constant and clear communication skills, as QBE is a very diverse company with diverse employees and backgrounds. Working with people from all professions and backgrounds has taught the importance of communication.
Data Science Intern
QBE Insurance
Sun Prairie, WI
05.2023 - 08.2025
- The main emphasis of the internship was creating predictive models to leverage business decisions.
- Worked closely with my manager to create insightful fraud detection models, improving in-house fraud detection in a beta environment by several claims a year.
- Structured and manipulated data to be compliant with the models.
- Used LGBM leaf-wise gradient-boosted decision trees as the final model.
- Optuna was used to help tune parameters and hyperparameters.
- Presented the final fraud detection model using metrics such as Precision @ K, ROC, and AUC to non-data science teams in a clear and concise manner, using powerful graphs and charts to fortify the ideas
Education
Bachelor of Science - Data Science
UW-Madison
Madison, WI05-2024
Bachelor of Science - Economics
UW-Madison
Madison, WI05-2024
Skills
- Machine learning
- Predictive modeling
- Data analysis
- Data visualization
- CI/CD pipelines
- Unsupervised learning
- Python
- R
- AI/LLM integration
- MLOps
- Docker and Kubernetes
- Azure Cloud Functions
Timeline
Machine Learning Engineer
QBE Insurance
01.2024 - Current
Data Science Intern
QBE Insurance
05.2023 - 08.2025
Bachelor of Science - Data Science
UW-Madison
Bachelor of Science - Economics
UW-Madison
Similar Profiles
Evonne DsouzaEvonne Dsouza
Liability Underwriter at QBE InsuranceLiability Underwriter at QBE Insurance
Paola IlluzziPaola Illuzzi
MANAGER OF LEARNING DELIVERY at QBE InsuranceMANAGER OF LEARNING DELIVERY at QBE Insurance
Jesus IglesiasJesus Iglesias
Independent Contractor at QBE Insurance , Farmers, Armed Forces InsuranceIndependent Contractor at QBE Insurance , Farmers, Armed Forces Insurance
Thomas "Mason" WilliamsThomas "Mason" Williams
Pharmacist at Walgreens Boots AlliancePharmacist at Walgreens Boots Alliance
Ella CookElla Cook
Lifeguard at City of MadisonLifeguard at City of Madison