Associate Data Scientist (MMM)
What's The Role
- 3+ years of relevant MMM experience (Practical 2+ years experience in long-term marketing mix modelling)
- Build long-term Marketing Mix Models (MMM) using advanced tools tailored to specific business challenges.
- Identifies the right set of models suitable for long-term MMM modeling and develops the right code / package to execute them
- Select appropriate modeling techniques and develop custom code/packages to implement them effectively.
- Lead data preparation, exploratory analysis, and iterative modeling processes specific to long-term MMM.
- Deliver actionable insights on how brand media impacts long-term brand equity, sales, and margins.
- Evaluate the scientific rigor and business relevance of complex long-term Marketing Mix Models (MMM). Possess a deep understanding of existing MMM frameworks and demonstrate the ability to leverage short-term MMM models into building long-term MMM models.
- Engage with Shell stakeholders and Line managers to ensure timely and quality project delivery.
- Strong proficiency in Python, SQL, Git, Databricks, and understanding of object-oriented programming principles.
What We Need From You
- Good knowledge of Marketing domain, ATL/BTL marketing and clear understanding of concepts like adstock/carryover, saturation etc.
- Proven experience in building MMM models to capture the long-term impact of Marketing on Sales and Brand Equity is a must.
- Strong programming skills in Python and SQL.
- Good to have - Understanding of data engineering concepts, including data pipelines, ETL processes, object-oriented programming and general software engineering principles to build scalable and reusable analytical products.
- Understands life cycle of a generic data science project (from problem statement to model deployment)
- Exposure to causal inference is a plus.
- Hands on experience with at least 2 MMM techniques below:
- Mixed-effects models (random and fixed effects)
- Hierarchical linear models
- Bayesian modelling (e.g., Bayesian MMM)
- Structural equation modeling (SEM)
- Regularized Regression techniques
- Ability to explain complex ML models and analytical concepts in simple terms to business stakeholders.
- Good storytelling and presentation skills to effectively communicate insights and influence decisions.
- Collaborate effectively with stakeholders, including line managers and cross-functional teams, to accelerate project delivery and ensure alignment with expectations.
