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Nov 10, 2026
Data Science
Remote
7 - 9 Years
Data Scientist (Marketing Mix Modeling – MMM)
Job ID:
MT167
Nov 10, 2026
Data Science
Remote
7 - 9 Years
Job Description
We are looking for an experienced Data Scientist specializing in Marketing Mix Modeling (MMM) to develop, implement, and optimize advanced statistical and machine learning models. The ideal candidate should have strong expertise in Python, statistical modeling, Bayesian techniques, forecasting, predictive analytics, and marketing effectiveness measurement.
The candidate will be responsible for building data-driven solutions to evaluate marketing channel performance, measure ROI, optimize marketing spend, and deliver actionable business insights.
Key Responsibilities
Design, develop, and implement Marketing Mix Models (MMM) using statistical and machine learning techniques.
Build predictive models, forecasting solutions, and optimization algorithms using Python.
Apply Bayesian and hierarchical modeling techniques for marketing analytics.
Analyze marketing channel effectiveness, contribution, ROI, and incremental impact.
Implement Adstock transformations and model non-linear media effects.
Develop marketing budget allocation and optimization strategies.
Perform data preprocessing, feature engineering, statistical analysis, and model validation.
Build and maintain scalable data pipelines using SQL and ETL processes.
Deploy, monitor, and maintain machine learning models in production environments.
Work with cloud-based ML infrastructure and MLOps practices.
Communicate analytical findings and provide actionable recommendations to stakeholders.
Required Technical Skills
Programming & Data Science
Strong proficiency in Python, Pandas, NumPy, and Scikit-learn.
Experience with statistical modeling, regression, and machine learning.
Strong understanding of forecasting and predictive analytics.
Marketing Mix Modeling & Analytics
Hands-on experience in Marketing Mix Modeling (MMM).
Knowledge of Bayesian and Hierarchical Modeling.
Understanding of Adstock transformations and non-linear media effects.
Experience in marketing channel contribution and effectiveness analysis.
Strong understanding of ROI, MROI, and Incrementality Analysis.
Experience in marketing budget allocation and optimization.
Database & Data Engineering
Strong SQL skills.
Experience with PostgreSQL.
Knowledge of ETL pipelines and data processing workflows.
Cloud & MLOps
Experience with AWS SageMaker, EC2, S3, and Lambda.
Knowledge of model deployment, monitoring, and optimization.
Experience with MLOps practices and production ML workflows.
DevOps & Visualization
Experience with Git, GitHub, CI/CD pipelines, and unit testing.
Data visualization experience using Matplotlib, Seaborn, and Plotly.
Preferred Industry Experience
Candidates with experience in the following domains will be preferred:
Marketing Technology (MarTech)
Advertising Technology (AdTech)
eCommerce
Marketing Analytics
Forecasting and Optimization
Advanced Analytics
Machine Learning and Predictive Modeling
The candidate will be responsible for building data-driven solutions to evaluate marketing channel performance, measure ROI, optimize marketing spend, and deliver actionable business insights.
Key Responsibilities
Design, develop, and implement Marketing Mix Models (MMM) using statistical and machine learning techniques.
Build predictive models, forecasting solutions, and optimization algorithms using Python.
Apply Bayesian and hierarchical modeling techniques for marketing analytics.
Analyze marketing channel effectiveness, contribution, ROI, and incremental impact.
Implement Adstock transformations and model non-linear media effects.
Develop marketing budget allocation and optimization strategies.
Perform data preprocessing, feature engineering, statistical analysis, and model validation.
Build and maintain scalable data pipelines using SQL and ETL processes.
Deploy, monitor, and maintain machine learning models in production environments.
Work with cloud-based ML infrastructure and MLOps practices.
Communicate analytical findings and provide actionable recommendations to stakeholders.
Required Technical Skills
Programming & Data Science
Strong proficiency in Python, Pandas, NumPy, and Scikit-learn.
Experience with statistical modeling, regression, and machine learning.
Strong understanding of forecasting and predictive analytics.
Marketing Mix Modeling & Analytics
Hands-on experience in Marketing Mix Modeling (MMM).
Knowledge of Bayesian and Hierarchical Modeling.
Understanding of Adstock transformations and non-linear media effects.
Experience in marketing channel contribution and effectiveness analysis.
Strong understanding of ROI, MROI, and Incrementality Analysis.
Experience in marketing budget allocation and optimization.
Database & Data Engineering
Strong SQL skills.
Experience with PostgreSQL.
Knowledge of ETL pipelines and data processing workflows.
Cloud & MLOps
Experience with AWS SageMaker, EC2, S3, and Lambda.
Knowledge of model deployment, monitoring, and optimization.
Experience with MLOps practices and production ML workflows.
DevOps & Visualization
Experience with Git, GitHub, CI/CD pipelines, and unit testing.
Data visualization experience using Matplotlib, Seaborn, and Plotly.
Preferred Industry Experience
Candidates with experience in the following domains will be preferred:
Marketing Technology (MarTech)
Advertising Technology (AdTech)
eCommerce
Marketing Analytics
Forecasting and Optimization
Advanced Analytics
Machine Learning and Predictive Modeling
Job Overview
Location
Remote
Job Type
Contract
Key Skills
Marketing Mix Modeling (MMM), Python, Pandas, NumPy, Scikit-learn, Statistical Modeling, Bayesian Modeling, Hierarchical Modeling, Regression, Machine Learning, Forecasting, Predictive Analytics, Adstock, Non-linear Media Effects, Marketing ROI, MROI, Incrementality Analysis, Marketing Budget Optimization, SQL, PostgreSQL, ETL, AWS SageMaker, EC2, S3, Lambda, MLOps, Model Deployment, Model Monitoring, Git, GitHub, CI/CD, Matplotlib, Seaborn, Plotly.