We pioneered the predictive analytics that helped the Obama campaign make history in 2008, and have nearly two decades of experience helping companies and campaigns accurately target their communication and marketing.
Adriana is a Data Analyst at HaystaqDNA, where she maintains internal data pipelines for predictive analytics and performs ad hoc analyses for clients. Adriana graduated from Lewis & Clark College with a B.A. in Math and Computer Science, with additional academic coursework in Political Science and research experience in redistricting data.
Alejandra is a Data Analyst at HaystaqDNA, where she currently works on redistricting projects and geographic analysis/ map making for clients. Alejandra graduated from the University of Miami with a B.A. in History, minors in Political Science and Anthropology, and additional coursework in German and Russian. In her free time, Alejandra enjoys reading gothic horror novels and drinking copious amounts of coffee.
Andrew has over a decade of experience helping clients in the public and private sectors turn complicated data sets into actionable results. His expertise has benefited races at all levels including Obama for America, Bloomberg for Mayor, the Democratic Senate Campaign Committee, as well as a variety of international electoral campaigns. In his role at Haystaq, he is responsible for overseeing client engagements, as well as managing the firm’s operations. Prior to joining to Haystaq, Andrew was Vice President of Strategic Services at Strategic Telemetry, and before then a Vice President at KRC Research with responsibility over financial and field matters. An expert in research operations, he has overseen the implementation of hundreds of focus groups and surveys on six continents. Andrew previously served in the Clinton Administration as an aide to the U.S. Secretary of the Interior. A Wisconsin native, Andrew received an MBA from Johns Hopkins University and a B.A. in Economics and Politics & Government from Ripon College. When not consuming political news for fun, he turns his attention to the Green Bay Packers.
Andrew is a Junior Analyst from Seattle, WA. He is a graduate student at Stanford studying Management Science & Engineering and Data Science. He brings 5+ years of tech and non-technical experience in political campaigns, redistricting, and consulting.
Blake Silberberg is Director of Media Analytics at HaystaqDNA, where he focuses on using a wide array of technologies to help conduct detailed analyses. He also supports and maintains internal data systems and tools. Blake graduated from the University of Rochester with a B.A. in Political Science and additional academic and research experience in Computer Science and Film and Media Studies. Blake also earned a MS in Data Analytics from the University of Maryland Global College. When not absorbed in computers or politics, Blake enjoys playing Ultimate Frisbee and cheering on the Baltimore Orioles.
Brad leads a portfolio of client engagements and the company’s development of analytic products. Prior to joining the company, Brad has spent 20 years working for a variety of software and Internet companies, in roles ranging from programming to management. After getting his MBA, Brad has primarily worked in senior product management roles. His work experience includes a diverse range of systems and markets including domain registration, navigation, search engines, media asset management systems, fantasy sports websites, government procurement systems, and automated scanning and claims processing systems. Brad’s wide-ranging expertise in grappling with and deriving insights from large and rapidly changing data sets has positioned him to tackle the wide variety of unique challenges he handles at Haystaq. Brad has a Bachelors in Computer Science from Middlebury College and a MBA from UCLA Anderson.
Kate is the Director of the Redistricting Data Hub project at HaystaqDNA. She was previously a tenured associate professor of political science at St. John Fisher University in Rochester, New York.
Haystaq co-founder and CEO Ken Strasma is a pioneer in the field of predictive analytics in high-stakes Presidential campaigns. He began his career in politics in 1986, running a successful statewide campaign, and the served as the director of state legislative caucuses in Wisconsin and Minnesota. In 1997, he moved to Washington DC and became the Research Director for the National Committee for an Effective Congress, where he produced geographic targeting for Democratic candidates for virtually every office in the country. In 2003, Ken launched his own firm, Strategic Telemetry to focus on individual level predictive modeling. Ken served as the national targeting director for John Kerry’s presidential campaign 2004, and again for President Obama’s 2008 campaign. Ken’s firm, Strategic Telemetry developed the predictive models that propelled then-Senator Barack Obama to a dramatic victory over Hillary Clinton in the Democratic primaries, and then a historic winning campaign for the White House. His work also provided the analytic guidance to Michael Bloomberg’s 2009 re-election campaign as well as hundreds of statewide and congressional races and international campaigns on four continents.
In 2012, Ken launched HaystaqDNA, a firm that has been on the forefront of bringing political-style microtargeting to commercial clients. HaystaqDNA has worked for multiple Fortune 500 companies, and boasts a commercial client list with a combined market capitalization of over $600 billion. Ken has been a frequent speaker on the use of predictive analytics in politics and business, including keynoting the annual SPSS convention, and giving guest lectures at Princeton, Columbia and the University of Wisconsin. He has authored or has been the subject of numerous articles and studies on the subject in publications including the New York Times, the Harvard Business Review, The Atlantic, The San Francisco Chronicle, FiveThirtyEight.com and Campaigns and Elections Magazine. Ken is the author of an upcoming book on predictive analytics in politics that will be published by Cambridge University Press in late 2015.
Ken has three young daughters, so he has no free time, but if he did, he would once again indulge in his passion for Shakespeare, running, and adrenaline sports like skydiving and bungee jumping.
Peter is a Senior Data Analyst at HaystaqDNA working on the Redistricting Data Hub project. Peter graduated from Amherst College with a B.A. in Math and is pursuing a M.S. in Analytics from Georgia Tech.
Quentin is a Data Analyst at HaytstaqDNA, where he manages data and runs map based district reports. Quentin graduated from the University of North Carolina at Greensboro with a B.A. in Political Science with additional coursework at the Universität Mannheim, Germany. Quentin enjoys traveling when time permits.
Spencer is a Senior Data Analyst at HaystaqDNA working on the Redistricting Data Hub project. Spencer graduated from Macalester College with a B.A. in Geography and Anthropology, and a minor in Data Science. He completed his M.A. at McGill University. In his spare time, he enjoys baking and running.
Willie has nearly a decade of experience in helping campaigns and organizations harness the power of predictive analytics, including serving as project manager for modeling on the Obama for America campaign in 2008, managing Election Day boiler-rooms, and advising senior officials on dozens of campaigns. In 2011 and 2012, he served as the lead map drawing consultant to the Arizona Independent Redistricting Commission, and helped to shape the state’s Congressional and Legislative Districts. Willie has recently earned his MBA from Arizona State University, and he has a B.A. in Political Communication from The George Washington University.
Zach is a Data Analyst for HaystaqDNA. He has a degree in Geography with a minor in Geographic Information Systems from Texas Tech University. His free time is full of baseball, barbeque, Tex-Mex, and hiking.
We work with our clients to determine what we wish to predict and impact, then we collect data that can help make a difference.
Our team combines observations and opinions with our dataset of potentially thousands of indicators on any given individual.
Complex algorithms turn observations into models that can predict attitudes and behaviors.
We continually monitor everything we do to ensure the success of our models.