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# M-NAV Measurement Solutions Architect, Manager

- **Company:** Logic, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $87,400.0 - $293,800.0
- **Contract:** Permanent contract
- **Skills:** Data Architecture, Data Validation, R (Programming Language), Python (Programming Language), Logistic Regression, SQL Databases, Feature Engineering, Ontology Design, Model Validation, Marketing Cloud, Human in the Loop
- **Published:** October 28, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b564a1297ce58173

## About the Role

Knowledge of retail media networks (such as Amazon Ads and WalMart Connect) is a plus, as is fluency in coding in SQL in the AMC clean rooms to structure log-level data, validate schemas, harmonize taxonomy, engineer features, etc., * 5+ years in marketing measurement, econometrics, attribution, data science, or martech analytics; 3+ years working with clean rooms (such as LiveRamp, Google BQ), ad-platform data, or AMC-like environments. Experience should include:

 + Strong hard skills in SQL, Python or R, feature engineering, experimental design, model validation, MAPE/R²/F1 interpretation, taxonomy design, and data QA. Hands-on experience with "vibe coding" preferred.
 + Hands-on experience with statistical modeling techniques such as MMM, attribution, experimentation and familiarity with MTA, incrementality testing, bridge calibration, and privacy-safe measurement.
 + Experience leading analytic enagements and ability to translate analytical findings into value narrative for client.
 + Experience supporting sales teams in the role of a SME or in technical discussions with client is a must.
 + Strong soft skills: structured problem solving, ability to translate complex methods into clear business recommendations, stakeholder communication, and comfort working in governed, cross-functional delivery models.

## Description

We are looking for a hybrid Measurement Solutions Architect to improve the technical product features of Accenture Marketing Investment Navigator (M-Nav) AND operationalize, deliver and deploy the product for clients. Since M-Nav unifies measurement across MMM, user-level attribution, and experiments, the ideal candidate will have knowledge of advanced modeling methodologies such as Bayesian Regression, Bayesian Belief Networks, Gradient Descent, bagged logistic regression, regularized models as well as concepts around incrementality logic and MMM/MTA reconciliation.

The role partners with product development, data science, marketing/media stakeholders, and client teams to ensure models fit existing workflows, pass governance checks, and generate scenario-ready outputs for budget optimization. The role will deliver on the M-Nav vision: system-level MMM+MTA reconciliation, Amazon Marketing Cloud (or similar)-native measurement, feature engineering, model validation, human-in-the-loop governance, and decision-oriented outputs and not just math and modeling.

In addition, the role requires the ability to explain in plain business language the methodology and concepts used in building models so that clients can see the value of the technical outputs from M-Nav and how those outputs translate into ready-to-execute marketing and media investment decisions. The ideal candidate is fluent in explaining concepts related to statistical validation of data, building Bayesian models, feature engineering, optimization and simulation of budget scenarios.