Data Scientist

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