Data Science Manager

Role: Data Science Manager Market Mix Modelling (MMM)

About the Role

Were 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.

Youll own MMM programs end-to-end from raw data to executive-ready insights and play a key role in shaping how marketing decisions are made at scale.

What Youll Do

• Design, build, and deploy Marketing Mix Models from scratch for large-scale CPG clients
• Apply regression, time-series, Bayesian, and causal inference techniques to measure true media impact
• Lead MMM engagements end-to-end: data ingestion, modeling, validation, scenario simulation, and ROI optimization
• Translate complex analytical outputs into clear, actionable recommendations for senior business stakeholders
• Mentor and guide junior data scientists, ensuring high technical and delivery standards
• Continuously improve modeling approaches using modern ML, experimentation, and advanced statistics

What Were Looking For

• 812 years of experience in Data Science / Advanced Analytics
• 3+ years of recent, hands-on Market Mix Modeling experience
• Strong programming skills in Python and SQL
• Deep understanding of econometrics, regression, time-series analysis, and Bayesian methods
• Proven consulting or client-facing experience , with the ability to influence decisions
• CPG / FMCG domain exposure (mandatory)

Nice to Have

• Experience with Robyn, PyMC, Stan , or similar MMM frameworks
• Exposure to global / multi-market MMM programs
• Data visualization experience using Tableau, Power BI , or similar tools

Why This Role

• Work on high-impact, decision-critical problems for global brands
• Combine deep data science with real business influence
• Lead, mentor, and shape MMM practices at scale
• Competitive compensation aligned to impact and experience