- Build, calibrate, and refine Market Mix Models to measure the impact of marketing spend across channels (media, promotions, pricing, distribution)
- Translate MMM outputs into explicit, client-facing insights — attribution, ROI by channel, budget optimization scenarios
- Work closely with client business teams to understand marketing objectives and align model outputs to decision-making needs
- Validate model assumptions, run simulations, and present scenario analyses (what-if, budget reallocation)
- Clean, transform, and QA large marketing and sales datasets for modelling readiness
- Collaborate with internal analytics and consulting teams on deliverable packaging and storytelling
Qualifications:
- Market Mix Modelling (MMM): Hands-on model building experience — not just awareness. Exposure to Bayesian MMM or Robyn is a plus
- Python: Proficient — data manipulation, modelling pipelines, visualization (pandas, statsmodels, matplotlib/seaborn)
- SQL: Comfortable pulling and transforming data independently
- ML fundamentals: Regression, time-series, feature engineering — applied, not theoretical
- Client/consulting exposure: Ability to explain model outputs to non-technical stakeholders; slide-ready communication