Job Description
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 — and play a key role in shaping how marketing decisions are made at scale.
What You’ll 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 We’re Looking For
- 8–12 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, Py MC, 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
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 — and play a key role in shaping how marketing decisions are made at scale.
What You’ll 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 We’re Looking For
- 8–12 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, Py MC, 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
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