Scott Oddo

Designed and led the Responsible AI testing and validation paradigm for an LLM-powered clinical reporting module within a regulated software environment. Developed a real-time risk-scoring model predicting hypoglycemia onset up to 24 hours in advance for hospitalized patients.

Consulted on building an AI-powered personalized shopping assistant using implicit and explicit data.

Partnered with MIT researchers to develop neural network architectures demonstrating true continuous learning in real-world, non-stationary environments.

Built decision tree, random forest, and XGBoost classifiers predicting feature usage during enrollment to improve onboarding and retention. Quantified feature-level impact on first-renewal rates and developed customer lifetime value models and segmentation.

Led a 7-person cross-functional team of data analysts, data scientists, and data engineers. Built an AI churn-prediction model that reduced churn by 10% and developed segmentation, CLV, survival-curve, and price-elasticity models. Retained leadership through the 2021 merger and led consolidation of analytics infrastructure and ETL pipelines.

Built customer segmentation, product recommendation, and behavior-analysis models that improved usability and adoption of the website-builder product. Resolved enterprise-wide data fragmentation that had blocked cross-brand analysis.

Built an AI-driven product recommendation system based on purchase history. Used clustering to identify five key customer segments and correlated customer preference signals to power new personalized recommendation types.

Built a model predicting optimal send-time for client email marketing campaigns. Developed an NLP algorithm identifying the most effective subject-line keywords and generated cross-sell leads that increased add-on sales. Built ETL processes using Hadoop/Hive to integrate and analyze marketing data.

Led global product recommendation and personalization services deployed to 100MM+ devices across 15+ countries and 20+ languages. Grew the Nokia App Store from 1M to 11M downloads/day in 18 months and designed a tool enabling configuration of 20,000+ localized store versions at scale.

Built a scalable, AI-powered media-discovery network delivering personalization and product recommendations across music, movies, video, and blogs. Led a 5-person data science/engineering team plus cross-functional project teams.

Bachelor of Arts in Mathematics from Tufts University.

Grade: 3.76

PhD in Cognitive and Neural Systems from Boston University with a GPA of 3.76.

Master of Science in Mathematics from the University of New Hampshire.