Responsibilities :

- Build, calibrate, and refine Market Mix Models to measure the impact of marketing spend across channels (media, promotions, pricing, distribution).

- Translate MMM outputs into clear, 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.