Manager, Data Science (MMM)

Blend

Manager, Data Science with Media Mix Modeling

• Develop and deploy scalable machine learning models using Python
• Build and implement end-to-end MMM.
• Define and enforce best practices for model testing, monitoring, and deployment governance.
• Collaborate with data scientists, data engineers, product teams, and business stakeholders to deliver actionable ML solutions.
• Conduct model validation and performance evaluation, ensuring fairness, robustness, and reproducibility.
• Drive efficiency and scalability in MMM workflows through automation and distributed computing.
• Stay up to date with emerging trends in MMM, ML, MLOps, and Snowflake ecosystem to continuously improve solutions.
• Project management and the prioritize and manage multiple tasks effectively while managing, coaching and mentoring the team of 3 to 5 Analysts.

Qualifications:

• Proficiency in statistical modeling techniques

  , especially

  linear regression

  ,

  Bayesian models

  ,

  time series

  , or

  causal inference

  methods using Python, R
• Experience with

  MMM frameworks

  (e.g., Robyn, lightweight MMM, custom solutions).
• Knowledge of

  media metrics

  (e.g., impressions, GRPs, CPM, ROAS, etc.) and

  digital marketing channels

  (Facebook, Google Ads, TV, OOH, etc.).
• Deep understanding of

  model validation

  ,

  multicollinearity

  ,

  adstock/decay effects

  ,

  saturation curves

  .
• Experience with

  incrementality testing

  ,

  causal impact analysis

  , or

  A/B testing

  .
• Exceptional communication and presentation skills, with the ability to present findings, complex data insights and provide recommendations to the non-technical stakeholders in a clear and concise manner.
• Knowledge and experience with BI tools such as PoweBI, Tableau or Qlik Sense will be added advantage.