We are looking for a Data Scientist with strong expertise in Marketing Mix Modeling (MMM) to develop and deliver end-to-end marketing analytics solutions. The ideal candidate should have hands-on experience in building MMM models, media optimization, and stakeholder engagement. Experience in Brand Equity Modeling will be an added advantage.
The candidate should be proficient in Python, possess a strong understanding of marketing analytics concepts, and be capable of independently driving client engagements while delivering actionable business insights.
Design, develop, and implement end-to-end Marketing Mix Modeling (MMM) solutions.
Collaborate with business stakeholders to gather requirements and translate business objectives into analytical solutions.
Perform data collection, cleansing, preprocessing, exploratory data analysis (EDA), feature engineering, and model validation.
Develop both Short-Term and Long-Term Marketing Mix Models to measure marketing effectiveness.
Apply statistical and machine learning techniques to quantify media impact and marketing performance.
Build media budget optimization models and recommend optimal channel investment strategies.
Interpret model outputs and present actionable insights to business stakeholders.
Work closely with cross-functional teams to ensure successful deployment and continuous improvement of MMM solutions.
Develop scalable, production-quality Python code following software engineering best practices.
Maintain version control using Git and contribute to collaborative development workflows.
Drive stakeholder discussions independently and manage day-to-day project engagements.
4–6 years of experience in Data Science .
Minimum 3 years of hands-on experience in Marketing Mix Modeling (MMM) .
Strong experience in end-to-end MMM solution development, including:
Requirement Gathering
Data Processing
Exploratory Data Analysis (EDA)
Feature Engineering
Short-Term & Long-Term Modeling
Model Validation
Media Optimization
Strong understanding of marketing concepts including:
Adstock / Carryover Effects
Saturation Curves
Media Effectiveness Measurement
Marketing Attribution Concepts
Deep understanding of MMM methodologies, including:
Additive Models
Multiplicative Models
Bayesian Regression
Statistical Modeling Techniques
Strong expertise in media budget optimization and optimization algorithms.
Excellent programming skills in Python with experience writing production-quality code.
Experience using Git for version control.
Strong analytical, problem-solving, and communication skills.
Proven ability to manage stakeholders and independently drive project execution.
Experience with Brand Equity Modeling .
Exposure to advanced statistical modeling and Bayesian techniques.
Experience working with marketing analytics or consumer goods organizations.
Familiarity with cloud-based analytics environments is an advantage.
Marketing Mix Modeling (MMM)
Marketing Analytics
Media Budget Optimization
Bayesian Regression
Statistical Modeling
Python
Exploratory Data Analysis (EDA)
Data Processing
Stakeholder Management
Business Consulting
Production-quality Code Development
Git Version Control
