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

• 
  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.

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