Give data meaning. That’s what we’re all about. We created the kind of company we wanted to see in the world.

Data Scientists.

Analysts.

Researchers.

Storytellers.

We demystify data to help organizations make better decisions.

About

Gradient by the numbers:

200+

Customers
Served

700+

Reports
Delivered

950K+

Lines of Code
Written

600+

Surveys
Fielded

7+

Years
Running

The people behind the numbers

Tom Vladeck

Tom Vladeck

Managing Director // New York, New York

Tom was inspired to start Gradient by the cutting-edge market research performed by his advisors at Wharton, where he received his MBA in marketing and statistics. Prior to Wharton, Tom received a master’s degree from the London School of Economics and studied math at Pomona College. In a prior life, Tom produced quantitative models for global climate policy reports.

Kyle Block

Kyle Block

Head of Research // Philadelphia, Pennsylvania

Kyle is a global market researcher who studies behavior using a wide range of methodologies. He has designed hundreds of population and consumer studies in more than three dozen international markets, and his work has influenced global ad campaigns in emerging markets. An aficionado of maps and spatial data, Kyle holds a master’s in Spatial Analytics from the University of Pennsylvania and studied International Relations and Spanish at Claremont McKenna College.

Stefan Musch

Stefan Musch

Head of Product // ‘s-Hertogenbosch, Netherlands

Stefan holds a master’s degree in Marketing and Management from Tilburg University. After Tilburg, Stefan went into industry where he applied state-of-the-art marketing science methods to business challenges. Stefan partners with client teams to translate advanced analysis to easy-to-implement recommendations, guiding managers along the way.

Brendon Ellis

Brendon Ellis

Research Director // Chicago, Illinois

Brendon earned his master’s degree in Positive Organizational Psychology & Evaluation from Claremont Graduate University and is currently pursuing his PhD in Positive Organizational Psychology. He applies his background in survey research methods on a daily basis to help clients develop instruments that measure anything from attitudes and preferences to intentions and behavior.

Nina Sabarre

Nina Sabarre

Research & Evaluation Consultant // Washington D.C.

Nina has nearly a decade of experience in mixed-methods research and evaluation in over 25 countries for a wide range of public, private, and non-profit clients. She is known for helping clients make sense of complex problems and using data to advance systems change. Nina teaches Evaluation Approaches & Design as an adjunct faculty member of American University and is a PhD Candidate at Claremont Graduate Unversity.

Cory Manento

Cory Manento

Senior Research Manager // West Hartford, Connecticut

Cory holds a master’s degree and PhD in Political Science from Brown University, specializing in experimental survey research on voter attitudes, behavior, and electoral preferences. Coming from a background in which success is achieved through rigorous causal inference and sharp research design, Cory thrives on translating client needs into testable questions that yield actionable results.

Iaroslav Domin

Iaroslav Domin

Senior Statistical Programmer // Kharkiv, Ukraine

Iaroslav earned his master's degree in Applied Mathematics from V. N. Karazin Kharkiv National University. He started his career as a statistical programmer working in the field of clinical trials. Iaroslav is a passionate R programmer who loves working with data and helping other programmers by being a top contributor on StackOverflow.

Sarah Binns

Sarah Binns

Marketing Associate // Portland, Oregon

Sarah is a marketing professional with over a decade of experience in diverse industries. She is a passionate, creative storyteller who bridges the gap between statistical data and everyday understanding of that data. Sarah has an English degree from Mount Holyoke College.

Jordan Boeder

Jordan Boeder

Research Manager // Fort Collins, Colorado

Jordan received his master’s degree and Ph.D. in Developmental Psychology from Claremont Graduate University. After receiving his Ph.D., he worked as a Post-Doctoral researcher at the University of Zurich where he honed his skills in Bayesian data analysis. Jordan uses his years of teaching experience to help distill complex research findings into simple insights.

Emmanuel Ugochukwu

Emmanuel Ugochukwu

Data Scientist // Lagos, Nigeria

Emmanuel holds a bachelor's degree in Electrical Electronics Engineering from the Federal University of Technology, Owerri, Nigeria. He is a data scientist who enjoys connecting the dots, be it ideas from different disciplines or applications from different industries. He is an R lover who enjoys analyzing data and creating stunning visualizations.

Brandon Sutton

Brandon Sutton

Research Manager // Baltimore, Maryland

Brandon holds a master’s degree in Anthropology from Binghamton University where his research focused on local government, infrastructure, and local politics. He started his career as a market researcher working primarily for corporate and non-profit clients in the life sciences, technology, and industrial spaces across over a dozen international markets.

Amy Dennis

Amy Dennis

Operations Manager // Amsterdam, Netherlands

Amy has nearly a decade of experience in operations and project management. She is driven to keep systems running smoothly and predictably to empower team members to focus successfully on essential tasks. She holds a degree in New Media Communications from Oregon State University.

What’s in a name?

gradient noun

gra-di-ent | \ˈgrā-dē-ənt\

abbreviation: grad. Symbol: ∇

*Definitions provided by Merriam-Webster
  • 1

    the rate of change with respect to distance of a variable quantity, as temperature or pressure, in the direction of maximum change.

  • 2

    a curve representing such a rate of change.

  • 3

    a differential operator that, operating upon a function of several variables, results in a vector the coordinates of which are the partial derivatives of the function.