Data Scientist

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