I&P - GN - SONG - AI & Data - Marketing - MMM - Manager

Job Summary:
As a Marketing Mix Modeling (MMM) Manager, you will lead the design, development, and deployment of advanced media measurement and marketing effectiveness models to drive data-driven decision-making for clients. Your typical day will involve managing a team of analysts and consultants, collaborating with senior stakeholders, interpreting model outputs to generate actionable business insights, and guiding the adoption of open-source MMM frameworks such as PyMC, Meridian, and Robyn.

Roles & Responsibilities:
- Lead end-to-end development and delivery of Marketing Mix Models (MMM) using open-source frameworks including PyMC, Meridian, and Robyn.
- Manage, mentor, and guide a team of data scientists, setting clear objectives and ensuring high-quality model outputs.
- Collaborate with senior client stakeholders and cross-functional teams to translate business objectives into robust measurement strategies.
- Design Bayesian and frequentist MMM frameworks to evaluate media spend effectiveness, attribution, and budget optimization across channels.
- Oversee model validation, diagnostics, and testing to ensure reliability and business relevance of insights.
- Present findings and strategic recommendations to C-suite and senior business leaders in a clear, impactful manner.
- Drive innovation by staying current with advancements in MMM, media analytics, and open-source tooling, integrating best practices into team workflows.

Professional & Technical Skills:
- Must Have Skills: Hands-on proficiency in Marketing Mix Modeling (MMM) and media measurement techniques.
- Expertise in open-source MMM libraries: PyMC (Bayesian probabilistic modeling), Google Meridian, and Meta Robyn.
- Strong command of Python for statistical modeling, data wrangling, and visualization.
- Deep understanding of Bayesian inference, hierarchical models, and time-series analysis as applied to media and marketing data.
- Proven people management experience: leading, coaching, and developing data science or analytics teams.
- Strong stakeholder management and executive communication skills, with the ability to translate complex model outputs into business recommendations.
- Good to Have: Familiarity with cloud platforms (GCP, AWS, Azure), and media planning or attribution tools.
- Experience with experiment design (A/B testing, incrementality testing) and causal inference methods.

Additional Information:
- The ideal candidate will possess a strong background in quantitative disciplines (Statistics, Mathematics, Economics, or Computer Science) with a demonstrated track record of building and deploying MMM solutions for large-scale marketing measurement challenges.
- Prior experience managing teams of 3+ members in a consulting, agency, or analytics environment is strongly preferred.
- This position is based at PAN India offices.

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com 

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