M-NAV Measurement Solutions Architect, Manager

Accenture • New York, NY

3d • $80,400 - $293,800

About The Position

Accenture Song is hiring a hybrid Measurement Solutions Architect to enhance the technical product features of Accenture Marketing Investment Navigator (M-Nav) and operationalize, deliver, and deploy the product for clients. M-Nav is an AI-native, enterprise-scale platform that unifies marketing mix modeling (MMM), user-level attribution, sales lift, and brand lift. It combines Accenture’s attribution methodology with Amazon signals to help marketers make budget decisions, with initial deployments reporting business-outcome improvements of 17% and above at twice the speed of current approaches.

The role works with product development, data science, marketing and media stakeholders, and client teams. It ensures models fit existing workflows, satisfy governance checks, and produce scenario-ready outputs for budget optimization. The work advances system-level MMM and MTA reconciliation, Amazon Marketing Cloud (AMC)-native measurement, feature engineering, model validation, human-in-the-loop governance, and decision-oriented outputs.

The successful candidate will explain technical methods in clear business language and show clients how model outputs translate into executable marketing and media investment decisions. The position calls for fluency in statistical validation, Bayesian modeling, feature engineering, and budget-scenario optimization and simulation. Retail media network knowledge, including Amazon Ads and Walmart Connect, is a plus, as is SQL experience in AMC clean rooms.

Requirements

• At least 5 years of experience in marketing measurement, econometrics, attribution, data science, or martech analytics.
• At least 3 years working with clean rooms such as LiveRamp or Google BigQuery, ad-platform data, or AMC-like environments.
• Strong SQL and Python or R skills.
• Experience with feature engineering, experimental design, model validation, interpretation of MAPE, R², and F1, taxonomy design, and data quality assurance.
• Hands-on experience with statistical modeling techniques such as MMM, attribution, and experimentation.
• Familiarity with multi-touch attribution (MTA), incrementality testing, bridge calibration, and privacy-safe measurement.
• Experience leading analytic engagements and translating findings into a value narrative for clients.
• Experience supporting sales teams as a subject-matter expert or participating in technical client discussions.
• Strong structured problem-solving, communication, and stakeholder skills, including translating complex methods into clear business recommendations and working in governed, cross-functional delivery models.

Nice To Haves

• Hands-on experience with “vibe coding.”
• Knowledge of retail media networks such as Amazon Ads and Walmart Connect.
• Fluency in SQL coding in Amazon Marketing Cloud clean rooms.

Responsibilities

• Improve the technical product features of M-Nav.
• Operationalize, deliver, and deploy M-Nav for clients.
• Partner with product development, data science, marketing and media stakeholders, and client teams.
• Ensure models fit existing workflows, pass governance checks, and generate scenario-ready outputs for budget optimization.
• Support system-level MMM and MTA reconciliation, AMC-native measurement, feature engineering, model validation, human-in-the-loop governance, and decision-oriented outputs.
• Explain modeling methodologies and technical concepts in plain business language, connecting model outputs to actionable marketing and media investment decisions.
• Lead analytic engagements and translate analytical findings into client value narratives.
• Support sales teams as a subject-matter expert and participate in technical client discussions.
• Use SQL in clean-room environments to structure log-level data, validate schemas, harmonize taxonomy, and engineer features, where applicable.

Benefits

• Medical coverage
• Dental insurance
• Vision insurance
• Life insurance
• Long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed