Christophe Williams

Led data science consulting practice, focusing on data strategy and growth-oriented data services. Served as fractional chief data officer for early-stage startups: set strategy, built capabilities and products, hired talent. Supported user acquisition, forecasting, resource allocation, product development; specialized in fintech and SaaS companies. Offered the following services; strategy, governance, hiring data teams, architecture, predictive analytics, time series analysis, regression, classification, recommendation systems, machine learning, natural language processing, ETL, and pipelines

Served as general manager of hud.ai (the second oldest portfolio company within the Foundry.ai startup studio): led the product roadmap, data science, business development, and customer success. Built dozens of new feature sets/models across full stack, coordinating in-house and offshore developer teams and doubling sales. Executed pivot in product strategy, built new product and go-to-market strategy. Built NLP models with TensorFlow and Scikit-learn, deployed using Docker, Serverless/Lambda, and scaled with Node and elasticsearch. Developed new ETL process and built data pipelines from scratch for large text datasets, using Python, Selenium, AWS Lambda + Layers, and both Postgres and a data lake. Consulted for telecom company and built advanced predictive models for buying propensity, customer churn, and marketing campaign effectiveness. Built large competitive intelligence system using cloud-based crawlers, which along with first-party data were used to train and update predictive models.

Provided SaaS analytics services to water utilities to reduce lost revenue. Built most popular product, which forecasted resource usage and identified deviations in order to pinpoint equipment degradation. Built an MVP and beta app, launched in three pilot cities. Won third place at the Penn Wharton Startup Competition ($35,000), Summer Venture Award ($10,000), and Innovation Fund ($1,500).

Designed and built machine learning models to target grocery and CPG items to fast-growing Amazon shopper segments. Led partner teams around the world to implement and refine model, scaled to three international markets. Led process by coordinating technical and non-technical teams during scoping, development, and planning for roll-out.

Led acquisitions of high-spending consumers across the company’s flagship products, Venture and Quicksilver. Created an innovative model connecting the effects of offline and online marketing. Obtained a $10 million testing budget to conduct full analysis. Led a small team in the analysis of results. Delivered learnings that drive millions in annual value to the CEO and Board. Developed product strategy for market-leading cash rewards card, Quicksilver, growing new customers through digital channels by 40% annually. Designed and launched multi-million-dollar campaigns to acquire customers and build brand value in high-impact markets, coordinating a half-dozen internal and external teams. Promoted < nine months after joining the team. Oversaw credit card loss forecasting using advanced financial models in multi-billion-dollar credit portfolios. Managed biannual stress test of $70 billion in card loans, coordinating the process across 15 people, and producing whitepaper for the Federal Reserve.

Developed finely tuned models of voter turnout and candidate support in 2012 battleground states. Mined massive voter-level datasets with >1,000 data fields (demographics, voting history, household info, 3rd-party data). Discovered prediction discrepancies and created new models which overcame poor state data in key variables (e.g. age, party registration).