In my previous roles at Chime, Apple, and Uber, we had sophisticated analytics and machine learning needs as we set out to deliver big goals for our customers. No vendor could meet our needs, so my teams built many things in-house. One example that I'm proud of is Michelangelo - Uber's ML Platform. These technologies contributed to billions of dollars of incremental revenue.Now, I am setting out to do this with Palladio AI. We are addressing large, unmet needs in advanced revenue and retention analytics for Product leaders. We deliver AI-powered guidance on opportunities and gaps to inform and prioritize product iteration investments.I want to help product leaders experience the same joy of making magic for customers and the revenue impact that follows, as I experienced at Chime, Apple, and Uber.

As Chief Data Officer, I led Data Analytics, Data Science, Data Engineering, Machine Learning Platform and Forecasting.

Led the data science and analytics functions for Apple's autonomous technology efforts, including development of statistically rigorous protocols for evaluation of autonomous performance in real-world and simulation environments.

I advised companies and founders on strategy, especially addressing data science platforms, teams, and products.

Led Data Science strategy and execution for machine learning, system evaluation, data quality, and safety evaluations. Ghost is an autonomous vehicle startup in Mountain View, CA.

Led and launched many foundational efforts. In my final two years, I led the Safety Data Science team, which took on some of the hardest and highest priority challenges of the company by making rare events rarer.In addition, I launched and architected our teams and platforms for machine learning (Michelangelo) and marketplace forecasting, for demand & supply forecasting in high resolution of time and space (FutureFlow). These have been the foundation upon which scores of new applications have been developed, adding hundreds of millions of dollars of incremental annual revenue.Overall, I tackled strategic & tactical problems, both technical and organizational, that have included:* Architected Uber's platform for Machine Learning* Architected Uber's system for high resolution spatiotemporal forecasting* Started the ML Platform team and ML Data Science team* Manager of numerous data scientists developing machine learning and statistical models* Launched large new efforts and new teams, setting their vision and roadmaps* Recruited large numbers of statisticians and other quants* Recruited managers in: Product, Data Science, and Engineering. * Introduced substantial changes to DS recruiting processes, including interviews, outreach, campus & conference recruiting, and offers* Multiple patents awarded* Due diligence on external organizationsUber's rapid growth has given me the opportunity/responsibility to fill in for other roles at times: product manager, engineering manager, and recruiter.

I had two roles as a Strat (Quant): High frequency trading of interest rates products (Treasuries, Futures, etc.), and as a Divisional Strat. The Div Strats team is responsible for analyses and modeling of global activity - sales & trading - across all of the asset classes in Goldman's trading division.In HFT, I led the development of strategies that achieved more than 5X increase in profitability of the team's market making strategies, despite historically low benchmark interest rates. My team achieved >10X greater productivity using a modeling & deployment framework I developed.As a Div Strat, I led the Securities Division's efforts to aggregate, analyze, and leverage its overall trading volumes and market share data. I was responsible to the COO and CFO of the Securities Division. I led an effort spanning 8 asset classes, comprising 70 engineers, strats, and stakeholders.Notable achievements:- Led Strat due diligence on many FinTech investments and vendors, including two sizable investments- Designed framework & syntax for industrial machine learning and rapid deployment- Novel visualization methods for high resolution visualization of HFT order book & market activity- Novel visualization and algorithmic guidance for massive tabular time series data (for divisional CFO & COO reporting)- Started firmwide Data Science community, grew to ~300 people globally; had over 800 people by 2016- Conceived and defined a firm-wide data catalog, with leadership and development responsibilities shared across all major divisions

Developed the first profitable strategy at Teza. Focused on high frequency trading strategies across multiple asset classes. Developed modeling and deployment framework that enabled very rapid iteration cycles and reliable, efficient model deployment.

Led statistical and machine learning R&D in partnership with our chief medical officer, chief scientist, and leading medical research centers around the world. Designed machine learning and statistical research platform, data warehousing and complex event processing framework to deploy machine learning models.

The Ensemble tied for the highest score in the Netflix Prize Competition, a $1 million competition to develop the best recommendation system in the world.

Graduate summer associate in Process Driven Trading (PDT) group, and developed strategies for systematic trading.

Responsibilities and contributions included: development of summarization algorithms, global ranking quality metrics, improvements to freshness algorithms and metrics, web spam identification heuristics.Altavista was acquired by Overture, and Overture was acquired by Yahoo.

I developed new algorithms for document summarization, topic identification, and other areas of natural language processing and information retrieval. Also involved in technical presentations to secure angel and VC funding, recruiting, and mentorship.

Received full-tuition NSA scholarship and year-round stipend. Worked at the Agency during summers and after graduation. Worked in computational number theory, high performance computing and foreign languages (statistical machine translation). Selected for the Director's Summer Program (DSP).