MMM Data Scientist: Bayesian Marketing Mix Modelling

s360 A/S; Barcelona; On-site; EUR 65,000 - 90,000; Full time

Job summary

s360 seeks a Data Scientist based in Barcelona to lead Marketing Mix Modelling engagements from data questions to client-ready recommendations. You will work with Meridian, PyMC-Marketing and Robyn, applying Bayesian modelling and robust diagnostics to deliver actionable insights for senior stakeholders.

You will collaborate with Digital Growth, account teams and measurement specialists, managing data intake, priors, and priors selection while communicating uncertainty clearly to clients.

Qualifications

• Experience with Marketing Mix Modelling delivery end-to-end.
• Ability to translate model outputs into client-ready recommendations.
• Comfort in presenting to senior stakeholders in marketing and finance.
• Strong data validation and diagnostics to ensure model trust.

Responsibilities

• Own Meridian MMM delivery from data questions to client-ready recommendations.
• Collaborate with clients, growth teams, and measurement specialists to ensure sound results.
• Conduct calibration and validation tests, including holdout and incrementality checks.
• Turn ROI and budget optimisation insights into clear client guidance.
• Manage data intake and modelling workflows in cloud environments and notebooks.
• Scope proposals and model refreshes with leadership for client engagements.

Skills

Bayesian MMM

Client delivery

Diagnostics & judgment

Media understanding

Client communication

Cross-disciplinary collaboration

Tools

Meridian

PyMC-Marketing

Robyn

Google Cloud

AWS

Azure

Colab

Python

Job description

s360 seeks a Data Scientist based in Barcelona to lead Marketing Mix Modelling engagements from data questions to client-ready recommendations. You will work with Meridian, PyMC-Marketing and Robyn, applying Bayesian modelling and robust diagnostics to deliver actionable insights for senior stakeholders.

You will collaborate with Digital Growth, account teams and measurement specialists, managing data intake, priors, and priors selection while communicating uncertainty clearly to clients.