Data Cowboys is a boutique data science and machine learning consulting cooperative, offering custom expert-level solutions for complex data problems. Collectively, we have nearly two decades of academic and real-world experience in turning challenges into practical algorithms using a battery of machine learning, artificial intelligence, data science, and statistics tools, and we take pride in clearly communicating our results to audiences of all backgrounds.


    Deep Neural Networks for Natural Language Processing


    Citeomatic is a deep learning model for the citation prediction NLP task. You enter the title and abstract of an in-progress academic paper, and Citeomatic suggests other papers for you to review and potentially cite. It's specifically designed to learn a robust model that gives meaningful predictions, even when it’s wrong. We contributed to core algorithm design and development.


    This work appeared at NAACL '18. Read an intro here, and then try it yourself.


    Other results of our collaboration with AI2:

    This work is ongoing since March, 2016.

    Machine Learning Strategy Consulting


    The Healthy Birth, Growth, and Development (HBGD) program was launched in 2013 by the Bill & Melinda Gates Foundation.


    The Knowledge Integration (Ki) initiative aims facilitates collaboration between researchers, quantitative experts, and policy makers in fields related to HBGD. The broad goal is to aggregate data from past longitudinal studies about pathways and risk factors that affect birth, growth, and neurocognitive development in order to better predict Ki outcomes.


    Sergey works closely with Ki leadership - designing and overseeing data science contests; managing external collaborations with academic research labs and software companies; and modeling many diverse global health datasets.


    This work is ongoing since February, 2015.

    Official Partners


    Algorithmia is building a gigantic marketplace for algorithms. We are one of their certified partners for novel algorithmic development, working with their clients to design the machine learning algorithms hosted on Algorithmia's platform.

    Online Game Recommendation Engine


    Blastworks develops and publishes online games, with a large and growing list of content. We are helping them use behavioral data to develop a recommendation engine that provides their users with high quality suggestions for new games and creates greater exposure to their full catalog.

    Contributing to Technical Books


    Jenny Dearborn, Chief Learning Officer and Senior Vice President at SAP, has written Data Driven, a "practical guide to increasing sales success, using the power of data analytics," and The Data Driven Leader (with David Swanson), "a clear, accessible guide to solving important leadership challenges through human resources-focused and other data analytics."


    We helped her and her team come up with clear and compelling ways to communicate the deep mathematical models that are at the core of the book, as well as contributed to the plot and characterizations.

    Improving Reading Comprehension


    Actively Learn makes a reading tool that enables teachers to guide, monitor, and improve student learning. With our help, they wrote and were awarded an NSF SBIR grant to answer the key question: "How can we personalize reading instruction so as to increase comprehension & learning?" We are diving deep into the data with sophisticated machine learning tools, and bringing back testable hypotheses about what helps and hinders students.


    This work is ongoing since April, 2014.

    Bayesian A/B Testing


    RichRelevance swears by their top-notch recommendations. But what's the right way to measure their efficacy? Sergey put together an intuitive, comprehensive Bayesian A/B testing system that works for any KPI, and can provide direct answers to key customer questions like "What is the probability that algorithm A has at least 5% lift over algorithm B?


    Read all about this work in Sergey's three (archived) blog posts: [1], [2], and [3].

    Bandits for Online Recommendations


    The most important piece of RichRelevance's impressive big data pipeline is their core recommendation system. It serves thousands of recommendations every minute, and it has to learn quickly from new data. Working with their analytics team, Sergey engineered a modern bandit-based approach to online recommendations that learns from less data, adapts easily to any optimization metric, and does not compromise quality at production-scale.


    Three (now archived) blog posts describe the results of our research: [1], [2], and [3].


    Sergey Feldman

    Sergey Feldman has spent the last decade working with data and designing machine learning algorithms. He's done both academic and real-world data wrangling, and loves to learn about new domains in order to build the perfect solution for the problem at hand. Sergey has a PhD in machine learning from the University of Washington, and is also interested in statistics, signal processing, and natural language processing.


    Sergey is based in Seattle.

    Ilya Barshai

    Ilya Barshai has been working in risk and failure analysis of a wide variety of product designs for 8 years. He has extensive experience in the improvement of test lab processes through the development of automation tools and interfaces for electronic, mechanical and RF systems. He's also interested in predictive natural language processing. Ilya has a B.S. in electrical engineering from the University of Illinois at Chicago with a focus in control theory and signal processing, and has completed the Johns Hopkins Data Science specialization program.


    Ilya is based in Chicago.

    Dan Krupnik

    Dan Krupnik has worked in systems, lifecycle management, infrastructure design, and technical project management for the trading industry for over a decade. He is passionate about meeting client needs and providing flexible solutions to challenging problems. He specializes in defining project scope, right-sizing goals and milestones, and managing appropriate resources.


    Dan is based in Chicago.


    "We've really enjoyed working with Data Cowboys. I have explained our startup to hundreds of people and to this day Sergey and Ilya grasped what we do the fastest. Within minutes, our first conversation transitioned from context to idea generation, and it has been the same for every meeting since. They are professional, timely, and have a great sense of humor to boot. And they are so fast - both with their thinking and their output! Thanks to their efforts we have not yet had to hire data scientists in-house, saving us lots of money as well."

    Jay Goyal, CEO, Actively Learn

    "Sergey's machine learning consulting expertise has been invaluable to us at RichRelevance. He has a wonderful knack for quickly scoping a problem, alighting on a suitable machine learning solution, making efficient and early decisions on model choice and parameters, analyzing data, implementing solutions, and clearly communicating throughout the process. His solid grasp of Bayesian statistics, deep neural networks, online learning and optimization etc, and his ready and speedy application have produced significant and concrete value for us on many occasions."

    Apu Mishra, Lead Data Scientist, RichRelevance

    "Sergey has helped me with the writing of two books about data analytics: Data Driven and The Data Driven Leader. He's easy to work with, and provides well-considered and well-written results very quickly. While helping me with the technical aspects of my books, he consistently exhibited in-depth knowledge of analytics, machine learning, and data science, and he has the rare ability to communicate that knowledge clearly to readers at every level. I would be happy to recommend him to anyone requiring machine learning services of any kind."

    Jenny Dearborn, Chief Learning Officer, SAP

    "Sergey Feldman is the ideal combination you want in a consultant: he’s brilliant, knows his subject matter inside and out, and is great to work with – collaborative, candid and funny. He’s also typically lightning-fast, a straight shooter and accepts feedback readily and with grace. He also has a special gift for explaining complex analytical and other concepts in terms anyone can understand. I’d hire him again in a heartbeat, with total confidence that he will shine, get the job done right the first time and make me look great."

    Deb Arnold, Principal at Deb Arnold, Ink.

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