Testing & Validation Lead

Blend360•Columbia, MD

2d•$140,000 - $240,000

About The Position

Blend360 is looking for a Senior Manager, Intelligence Measurement & Validation to own the end-to-end testing program that demonstrates the value and effectiveness of a large-scale data monetization program. This role sits at the intersection of marketing measurement, data science, and data engineering, turning complex testing and analysis into clear, defensible evidence that helps our partners understand the impact of the program. You’ll own the full testing lifecycle—from defining the methodology and designing the test, through execution, analysis, documentation, and ultimately translating the results into partner-ready insights. You’ll lead backtests against historical campaign data, match-rate and audience coverage testing, and custom analyses designed to evaluate lift, correlation, calibration, and other measures of intelligence quality. This is a role for someone who is comfortable getting into the details of the analysis while also stepping back to understand the bigger picture, identify what the results actually mean, and communicate those findings clearly to both technical and business audiences. You’ll work closely with our Data Science and Data Engineering teams to translate test designs into rigorous analyses and ensure the underlying data and methodology stand up to scrutiny. Just as importantly, you’ll be responsible for turning those analyses into a compelling, defensible story—one that can be shared with partners and used internally to demonstrate the value of the program.

Requirements

5–7+ years of relevant experience in marketing measurement, media analytics, campaign measurement, attribution, data science, or a related analytical discipline.
Strong experience designing and executing testing and measurement methodologies, particularly backtesting, match-rate/audience coverage analysis, lift, and holdout testing.
Experience working within clean rooms for marketing analysis, measurement, and modeling activities
A solid understanding of marketing and media measurement and how campaign and audience data can be used to validate intelligence and demonstrate value.
Hands-on experience working with data and executing analyses—not simply defining requirements or reviewing someone else’s work.
Strong analytical judgment and the ability to distinguish between what the data demonstrates and what it does not.
Experience working cross-functionally with Data Science and Data Engineering teams.
The ability to take an ambiguous business question, create structure around it, determine the right testing approach, and drive it through to an answer.
Strong communication skills, with the ability to turn complex analytical results into clear, partner-ready stories.
Excellent documentation and project management skills, with a high degree of ownership and attention to detail.
A get-it-done mentality and the ability to manage multiple analyses and partner requests while maintaining rigor and quality.

Responsibilities

Own the end-to-end testing and validation lifecycle, including methodology, test design, documentation, execution, analysis, and readouts.
Develop and maintain testing methodologies for backtesting, match-rate and audience coverage testing, lift/holdout testing, and other validation approaches.
Lead the development of automation for testing methodologies in order to scale frequency of testing and improved consistency
Run tests and ad-hoc analyses within clean rooms, but owned and operated clean room and partner clean rooms
Run backtests that validate program intelligence against partners’ historical campaign and audience data.
Design and execute match tests to measure household match rates, audience coverage, and data quality.
Develop custom partner analyses, including correlation, lift, calibration, and other measurement approaches based on specific business questions.
Partner closely with Data Science and Data Engineering to translate test designs into executable analyses and ensure results are methodologically sound.
Analyze results and determine what the data can—and cannot—support, developing defensible conclusions and clear recommendations for next steps.
Translate complex analytical findings into concise, compelling partner-facing presentations and internal executive readouts.
Build and maintain clear documentation of testing methodologies, assumptions, processes, and results.
Identify opportunities to improve the testing framework, increase repeatability, and strengthen the evidence supporting the program's intelligence value proposition.
Serve as a subject-matter expert and thought partner across Marketing Measurement, Data Science, and Data Engineering.