Data Scientist - Demand & Pricing Analytics

Role: Data Scientist - Demand & Pricing Analytics

Experience: 3-6 years

Location: Bangalore (work from office)

About the Role: We are seeking a data-driven and analytical Data Scientist to join our team The ideal candidate will play a critical role in shaping data-backed strategies for demand forecasting, price optimization, and demand elasticity modeling across product lines and sales channels.

Key Responsibilities:

• Demand Forecasting:

Develop and maintain advanced time-series or ML models to predict demand at SKU, category, and regional levels using historical sales, seasonality, promotions, and market trends.

• Price Optimization:

Build dynamic pricing models to identify optimal price points, incorporating competitor analysis, elasticity, and inventory positions to maximize revenue and margins.

• Demand Elasticity Modeling:

Analyze how price changes affect consumer demand across segments using statistical techniques and machine learning.

Collaborate with product, merchandising, finance, and marketing teams to integrate insights into business decisions.

Automate data pipelines and build dashboards for stakeholders to visualize forecasts and pricing scenarios.

Conduct A/B testing and simulation modeling to validate forecasting and pricing strategies.

Required Skills & Experience:

• Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Applied Mathematics, or related fields.
• 3+ years of experience in retail analytics, pricing science, or demand forecasting.
• Proficient in Python/R, SQL, and relevant libraries (e.g., Scikit-learn, Statsmodels, Prophet, XGBoost).
• Cloud platform - Azure.
• Strong understanding of econometrics, elasticity models, and optimization techniques.
• Excellent communication skills with the ability to present complex insights to non-technical stakeholders.

Preferred Qualifications:

• Experience in fashion, footwear, or consumer goods industry.
• Familiarity with supply chain and inventory dynamics in retail.
• Knowledge of reinforcement learning or revenue management frameworks.