Data Science Manager – Market Mix Modelling (MMM)

Role: Data Science Manager – Market Mix Modelling (MMM) About the Role We’re hiring a Data Science Manager – MMM to drive next-generation marketing effectiveness analytics for global CPG and consumer brands . This role is built for a hands-on data science leader who enjoys solving complex, real-world business problems using econometrics, causal modeling, and machine learning , while working closely with senior stakeholders. You’ll own MMM programs end-to-end — from raw data to executive-ready insights, ensuring that our clients receive actionable recommendations that drive growth and revenue. Key responsibilities include: • Developing and maintaining market mix models (MMM) for global CPG and consumer brands, leveraging econometrics, causal modeling, and machine learning techniques. • Collaborating with cross-functional teams to integrate MMM insights into marketing strategies, driving business outcomes and ROI. • Designing and implementing data-driven solutions that drive growth, revenue, and customer engagement. • Developing and maintaining relationships with senior stakeholders, ensuring that MMM insights are actionable and impactful. • Staying up-to-date with the latest trends and advancements in machine learning, econometrics, and causal modeling to continuously improve MMM capabilities. About Us We’re a global leader in marketing effectiveness analytics, dedicated to helping CPG and consumer brands drive growth and revenue through data-driven decision-making. Our team of experts is passionate about solving complex business problems using cutting-edge analytics and technology. What We Offer • Competitive salary and benefits package • Opportunity to work with a talented and diverse team of data scientists and analysts • Collaborative and dynamic work environment • Professional development opportunities, including training and mentorship programs • Flexible working arrangements, including remote work options • Access to the latest tools and technologies in machine learning, econometrics, and causal modeling