About the Role :

We are looking for an experienced Associate Lead Data Scientist with strong Revenue Growth Management (RGM) expertise to work on advanced analytics and machine learning solutions for commercial business problems. The ideal candidate should have hands-on experience in pricing, promotions, demand modeling, and commercial analytics, along with strong stakeholder management and client-facing experience.

Key Responsibilities :

- Develop and implement Revenue Growth Management (RGM) solutions to drive pricing and promotion decisions.

- Build analytical models for Price Pack Architecture (PPA), Price Elasticity, Promotion Effectiveness, Revenue Decomposition, Demand Modeling, and Marketing Mix Modeling (MMM).

- Work with large-scale sales, shopper, retailer, POS, NielsenIQ, Circana/IRI, and syndicated datasets.

- Apply statistical modeling, machine learning, and causal inference techniques to solve commercial business problems.

- Translate analytical findings into actionable recommendations for Sales, Marketing, Finance, and Commercial teams.

- Engage directly with clients to understand business challenges and deliver data-driven solutions.

- Lead analytics projects, mentor junior team members, and drive successful project execution.

- Collaborate with cross-functional teams to build decision-support tools and scenario-planning solutions.

- Manage stakeholder communication, project reviews, and delivery governance.

Required Skills :

- 3-7 years of experience in Data Science, Analytics, or Machine Learning with mandatory Revenue Growth Management (RGM) experience.

- Hands-on experience in :

1. Price Pack Architecture (PPA)

2. Price Elasticity Modeling

3. Promotion Effectiveness

4. Revenue Decomposition

5. Demand Modeling

6. Marketing Mix Modeling (MMM)

7. Trade Promotion Analytics

8. Commercial Analytics

- Strong experience working with NielsenIQ, Circana/IRI, POS, Retailer, Shopper, or Syndicated Data.

- Proficiency in Python, SQL, R, Spark, NoSQL.

- Experience with Machine Learning techniques and statistical modeling.

- Exposure to cloud platforms such as AWS, Azure, or GCP.

- Strong communication and stakeholder management skills.