Job Title: Data Scientist – Marketing Mix Modeling (MMM)

Job Summary

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.

Key Responsibilities

- 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.

Required Skills

- 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

- Solid 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.

Preferred Qualifications

- 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.

Key Competencies

- 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

📌 Data Scientist (Bengaluru)
🏢 Indium
📍 Bengaluru