My Work

Product Analyst, Churchill Downs Interactive Canada

December 2021 - Jan 2025

Developed a churn prediction model using Python (Scikit-learn, Logistic Regression) and A/B testing, integrated with Braze, increasing player retention by 21% and tracking metrics like engagement and retention.

Built a predictive model with Python (Pandas, XGBoost) to identify and grow VIP players by 15%, collaborating with Marketing for personalized campaigns and leveraging MS SQL Server for efficient data querying.

Designed live MicroStrategy dashboards for major events (e.g., Kentucky Derby), boosting turnover by 12% through actionable insights on event engagement; integrated data via API with ZenDesk for cross-team visibility.

Analyzed marketing promotions with SQL and Google Optimize for A/B testing, achieving an 86% retention rate and driving a 10% monthly revenue increase, focusing on metrics like conversion rates and customer lifetime value.

Automated promotional credits and ad-hoc requests with Python scripts and AWS Lambda, enhancing efficiency by 15% and achieving 99% accuracy, while using Git/GitHub for version control.

Optimized the TwinSpires Loyalty program with statistical analysis (Statsmodels), saving $65,000 monthly through data-driven reward refinements, monitored via MicroStrategy dashboards.

Product Analyst, Triple Tree Nurseryland

September 2020 - December 2021

Conducted cohort analysis with Python (Pandas) and SQL on customer data, increasing repeat rates by 20% and monthly revenue by $20,000, focusing on metrics like retention and average order value.

Optimized email campaigns via A/B testing using Optimizely, improving open rates by 12% and click-through rates by 23%, tracking performance with Google Analytics integration.

Enhanced demand forecasting with statistical methods (Statsmodels) and R, reducing backorders by 17% and improving supply chain efficiency, with results visualized in Tableau for stakeholder review.

Performed market basket analysis using Python (NumPy) and SQL, lifting sales by 11% through segmentation and product pairing insights, leveraging AWS S3 for data storage and retrieval.

Data Analyst, QAD Inc

September 2020 - December 2021

Developed reusable documentation and knowledge assets using Jupyter notebooks and Google Workspace, significantly improving team productivity and onboarding.

Cleaned and validated large datasets with SQL and Python (Pandas), ensuring accuracy for analytics and reporting, and enforcing data governance practices akin to modern standards like Snowflake.

Senior Product Analyst, Flodata Networks

Feb 2025 - Present

Leveraged Python (Pandas, NumPy), SQL, and Tableau to analyze product usage data, focusing on SaaS metrics like feature adoption, user retention, and engagement, informing scalable product strategies.

Utilized AWS Glue for data transformation and S3 for scalable storage, collaborating with finance and product teams to build self-service analytics solutions that democratized data access.