Data Scientist

Role Overview

Develop, implement, and optimize Marketing Mix Models (MMM) to measure the impact of marketing investments across channels and support budget allocation decisions. This role involves building robust Bayesian statistical models, applying causal inference methodologies, and designing advanced statistical modelling techniques to drive marketing optimization strategies.

Responsibilities

• Develop, implement, and optimize Marketing Mix Models (MMM) to measure marketing investment impact.
• Build robust Bayesian statistical models for forecasting and scenario planning.
• Apply causal inference methodologies to measure incremental impact.
• Design and execute advanced statistical modelling including regression and time-series analysis.
• Develop attribution and incrementality measurement frameworks.
• Conduct hypothesis-driven experimentation, including A/B testing and geo experiments.
• Analyze large-scale marketing datasets to generate actionable insights.
• Build automated dashboards using Power BI or Looker Studio.
• Collaborate with cross-functional teams to translate findings into strategies.
• Build scalable Python-based analytics pipelines.
• Present statistical findings and recommendations to stakeholders.

Requirements

• 3–6 years of experience in Marketing Analytics, Marketing Science, Applied Data Science, Econometrics, or Media Analytics.
• Strong experience in agency, consulting, or digital marketing analytics environments.
• Expert knowledge of Marketing Mix Modelling (MMM).
• Strong understanding of Bayesian Inference.
• Expertise in Statistical Modelling (Linear, Multivariate, Hierarchical, Time-Series, Econometric).
• Hands-on experience with Causal Inference (Difference-in-Differences, Synthetic Control, Propensity Score Matching, etc.).
• Strong Python programming skills (pandas, NumPy, SciPy, scikit-learn, PyMC, Statsmodels).
• Strong SQL skills.
• Experience with Power BI or Looker Studio.

Skills

• Python
• SQL
• PyMC
• Bayesian Inference
• Statistical Modelling

Nice to Have

• Experience with Google Meridian Marketing Mix Modeling Framework.
• Knowledge of GeoLift, LightweightMMM, or Robyn.
• Experience with GCP, BigQuery, or Vertex AI.
• Knowledge of MLflow, Airflow, Docker, and CI/CD.
• Familiarity with Generative AI for reporting automation.