Data Scientist - MMM

Prescienceds; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Benefits offered by this job

Competitive salary

Performance‑based bonuses

Collaborative environment

Job summary

Prescienceds in Bengaluru seeks an experienced Marketing Mix Modeling (MMM) professional to build long‑term MMMs and translate insights into business actions.

The role requires 4+ years MMM, strong Python/SQL, Databricks, and stakeholder engagement to deliver models measuring the impact on sales, brand equity, and margins.

Qualifications

• 4+ years of MMM experience, including 2+ years in long-term MMM
• Strong Python and SQL skills for analytics
• Experience with Databricks and Git for collaboration
• Ability to translate complex modeling results into actionable insights
• Understanding of adstock/carryover, saturation, and long-term marketing effects
• Capable of stakeholder management and delivering on timelines

Responsibilities

• Build long-term Marketing Mix Models (MMM) using advanced tools
• Identify and implement suitable modeling techniques for long-term MMM
• Lead data preparation, exploratory analysis, and iterative modeling
• Deliver actionable insights on impact of brand media on sales and margins
• Evaluate rigor and relevance of complex MMMs and connect to business decisions
• Engage with stakeholders and cross-functional teams to drive delivery

Skills

MMM expertise

Python

SQL

Databricks

Git

OO programming

Stakeholder management

Storytelling

Presentation skills

Tools

Databricks

Job description

As an equal opportunity employer, we are dedicated to fostering a diverse and inclusive workplace, free from discrimination based on caste, religion, gender, sexual orientation, nationality, or other protected characteristics.

Role Overview

Seeking an experienced Marketing Mix Modeling (MMM) professional with 4+ years of relevant experience, including 2+ years in long‑term MMM, to develop and evaluate advanced models that measure the long‑term impact of marketing on sales, brand equity, and margins. The role requires strong expertise in MMM methodologies, Python/SQL‑based analytics, stakeholder management, and the ability to translate complex modeling outcomes into actionable business insights.

Job Description

• 4+ years of relevant MMM experience (practical 2+ years in long‑term marketing mix modelling)
• Build long‑term Marketing Mix Models (MMM) using advanced tools tailored to specific business challenges
• Identify the right set of models suitable for long‑term MMM and develop the appropriate code/package to execute them
• Select appropriate modeling techniques and develop custom code/packages to implement them effectively
• Lead data preparation, exploratory analysis, and iterative modeling processes specific to long‑term MMM
• Deliver actionable insights on how brand media impacts long‑term brand equity, sales, and margins
• Evaluate the scientific rigor and business relevance of complex long‑term Marketing Mix Models (MMM)
• Possess a deep understanding of existing MMM frameworks and demonstrate the ability to leverage short‑term MMM models into building long‑term MMM models
• Engage with stakeholders and line managers to ensure timely and quality project delivery
• Strong proficiency in Python, SQL, Git, Databricks, and understanding of object‑oriented programming principles

Requirements

• Good knowledge of Marketing domain, ATL/BTL marketing and clear understanding of concepts like adstock/carryover, saturation, etc.
• Proven experience in building MMM models to capture the long‑term impact of Marketing on Sales and Brand Equity is a must
• Strong programming skills in Python and SQL
• Good to have: understanding of data engineering concepts, including data pipelines, ETL processes, object‑oriented programming, and general software engineering principles to build scalable and reusable analytical products
• Understands the life cycle of a generic data science project (from problem statement to model deployment)
• Exposure to causal inference is a plus
• Hands‑on experience with at least 2 MMM techniques below:
  • Mixed‑effects models (random and fixed effects)
  • Hierarchical linear models
  • Bayesian modelling (e.g., Bayesian MMM)
  • Structural equation modeling (SEM)
  • Regularized Regression techniques
• Ability to explain complex ML models and analytical concepts in simple terms to business stakeholders
• Good storytelling and presentation skills to communicate insights effectively and influence decisions
• Collaborate effectively with stakeholders, including line managers and cross‑functional teams, to accelerate project delivery and ensure alignment with expectations
• Competitive salary and performance‑based bonuses
• Collaborative and supportive work environment
• Chance to learn and grow with a talented team