Data Scientist2021 - 2021The Spur Group
Technologies: Natural Language Processing (NLP), Keras
- Built binary and multi-class NLP models to determine violations for vitamin supplement reviews.
- Explored the entire history of available data to select the most appropriate training and validation data sets.
- Uncovered data issues relating to change in business practices and explained how this relates to model performance.
Principal Data Scientist2014 - 2021Data Science Evolution
Technologies: Bayesian Inference & Modeling, Data Mining, Jupyter Notebook, Python, SQL
- Modeled compensation distributions (5th, 25th, median, 75th, 95th percentiles) using Bayesian Networks on limited data fields, exceeding the performance of a much more complicated champion model.
- Built second-party fraud models in the automotive lending space on behalf of lenders, uncovering bad dealerships and other actors.
- Used health insurance claims data to understand the effects of new pharmaceuticals in the pharmaceuticals marketing space.
- Created semi-supervised segmentation for health care professionals based on their propensity to prescribe newer treatments.
Lead Data Scientist2016 - 2018SteppeChange
Technologies: Python, Apache Hive, Spark SQL, Customer Segmentation, CatBoost, XGBoost, Scikit-learn
- Built a series of solutions for customer personalization in the telecommunications space for a large EU telecommunications client, serving 20 million customers.
- Led several parallel use cases in course of the data management platform project with terabytes of daily data.
- Created models to determine the probability of a customer exceeding their voice, text, and data allotments. Incremental spend expectation once this threshold was exceeded.
- Analyzed whether a customer was rationing their usage to manage their allotted thresholds.
- Used the outputs of the models and other data to create the next best offer recommendations and pricing, keeping in mind the overall impact on the business.
VP, Data Science2011 - 2014LexisNexis Risk Solutions
Technologies: Fraud Prevention, Credit Risk, Management, Leadership, Mentorship & Coaching, Team Building, Executive Presentations
- Built and led a team of highly skilled data scientists and engineers to solve challenging problems for well-known financial, retail, and wireless institutions.
- Collaborated with the product organization to develop next generation credit risk and fraud models and attributes, seeking to derive incremental and unique value from internal data sources combined effectively with third-party data.
- Advanced research and development efforts, including cutting-edge custom modeling algorithm development, creation and adaptation of new data sources, and developing new verticals.
- Created a proof-of-concept to uncover Federal and State tax identity fraud to combat a multimillion-dollar problem where bad actors were using other people's personal identities to get returns sent to them.
- Calculated the Customer Lifetime Value and built attrition models on LifeLock customers.
Director, Analytics2006 - 2010First Data
Technologies: Machine Learning, Consulting, Team Leadership, Information Retrieval, Cluster Analysis, Predictive Analytics, Text Analytics, Natural Language Processing (NLP), Marketing Analytics
- Led custom analysis in the financial services space, building client-specific models and taking the problem from raw data to the final solution, anticipating business requirements and suggesting alternative approaches when necessary.
- Created marketing strategies for a top, frequent flier loyalty program, building consumer clusters and models looking to predict response to a given promotion, designing experimental campaigns, and scoring prospects to optimize new offers.
- Solved a payment reversal risk model problem by applying outside-the-box thinking on a subprime portfolio at a mid-sized US bank. Saved the client a minimum of $2.4 million per year, and provided the breakthrough in our sales process.
- Built a solution for a top 10 US bank in the fraud space that enabled our client to determine which credit card numbers may have been compromised using a skimming device at a gas pump.
- Collaborated with software engineers in developing, prototyping, and integrating state-of-the-art statistical and machine learning algorithms into enterprise analytics software.