Strategic and Quantitative Consulting


Your data drives your product. I help drive your data.

The real ROI in Data Science comes from having a holistic strategy between your data, product, and business needs along with a cohesive operational and people strategy.

Data Science isn't just about the algorithms.

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Talk to me about your survey design, A/B testing, quality control, performance optimization, statistical testing and design needs, among other things.

Having a performance and measurement strategy interlaced with your product's design means that you can respond to changes in market demands as they happen rather than running costly ad-hoc and impromptu "health check" surveys and tests.

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I can create or refine your game's math models --- from game economies and mechanics to paytables to leveling systems for card games, slots, board games, and sports betting.

Your game's mathematical backend matters just as much as its artistic UI.

Draw your players in with amazing visuals, but keep them playing with mathematically beautiful game design.

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Your data drives your product. I help drive your data. Before you take the Data Science plunge, or if you already have and can't extract that value that you are seeking, let me work with you about your Data Science strategy.


  • What data-oriented business questions need to be answered that require the use of advanced statistics, machine learning, computer vision, AI, etc.?
  • What types of projects / products can an investment in data science lead to?
  • What existing projects / products can be enhanced through data science work?

  • Data & Technology Strategy
    • What data science relevant data exists?
    • What relevant data should / could be curated?
    • What additional technologies are needed to support data science work in the near-term? in the long-term?


  • What should a data science team look like? required skills, domain expertise?
  • Where should it live within the organization and what business domains should it own?
  • How could data science interact / interface with the company's various business and technology units?


  • There are many ways that a data science team struggles within an organization. It is important to set expectations on all ends about the nature of data science initiatives --- unlike technology work which tends to be more deterministic and follows well-established product development life cycle processes (Agile, eg), data science work needs a different operational framework because of its venture-like nature, at least initially.
  • An internal education process with stakeholders will always be helpful before leaping in with data science.
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One of the hardest things to do well is understanding causation and correlation in your product. Whether you are looking to understand if your marketing campaign really did get that incremental lift you were seeking or if you want to understand which product features provide the most engagement, I can help.

Talk to me about your survey design, A/B testing, quality control, performance optimization, statistical testing and design needs, among other things.


Abstractly, performance is a function of many variables. For example, user retention for your mobile app is dependent on your user acquisition costs, your targeting demographics, and your own new user onboarding experience, among other things. Don't expect cheaply bought users to be retained. But at the same time, there is a diminishing return on retention as your user acquisition costs increase.

  • Understand the variables that affect product performance.
  • Have a clear, quantitative definition of performance! Performance tracking initiatives miss this point! We all know what performance means, intuitively. It's a much harder task to cleanly define it.
  • While both aggregate and relative measures are useful for tracking performance, it's also necessary to understand performance through several key measures to understand trade-offs.


In a complex product, measurement of practically anything worth measuring is notoriously difficult. Not only are there constant environmental changes (regular deploys by Engineering, eg), but a complex product also has several moving parts that interact with each other. For example, a SaaS product may have may allow a user to navigate through many features in an "open world" manner. Or a mobile game's design may preclude the possibility of shepherding players through a particular UX. Identifying relevant measures and relevant measurement points in your product is paramount to understanding what next steps to take.

  • Statistics matter, too! Not having enough sample points can provide false signals. Not having an a priori success or failiure criterion can lead to self-fulfilling prophecies.
  • It's easy to compute "measurement" from the data, however, what we measure is of much greater importance.
  • Knowing what to measure and reconciling against what can be measured, will be your north star when working through your product strategy.
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I offer consulting services for sports betting, lottery, slot math, reel strip design, table game math, online gaming, designing game economies, regulatory consulting, etc. Poker, Video Poker, Blackjack, Pai Gow, Baccarat, Bingo, Keno, Craps, Slots, Roulette, etc.

I'm also a general one stop shop for your product analytics needs: quality assurance, user / customer analysis, monetization optimization, sales and marketing strategies.

I help fine tune gaming products through a data-driven approach. Whether it is about understanding player behavior, app monetization, sales strategies, game design, the regulatory process, or quality assurance, I am here to help


RTP, hit rate, & volatility (and their equivalents) are usually what will come to mind if you're in the (social) casino space. Be it a slot game, a card game, or even a sports betting system you are making, getting the right balance between how much your players win, how often they win, and how big they win is the first step to getting a game from good to great. What are the other parts?

  • If you have a "leveling" system, it's important to know how your players will progress. How long will it take in terms of game actions? in terms of real time commitment? Are there retention bottlenecks caused by your player progression path?
  • Your game economy is your lifeblood! There's cheating (hacks and other technical bugs) and then there's exploiting broken game economies. In complex games where different game elements interact with each other and there are multiple in-game currencies, the potential for arbitrage increases. A careful management of your game economy can lead to a significant boost to your game's monetization.
  • Your players have their own price discrimination points. How do you currently learn that?
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