Data Scientist Demand & Pricing Analytics

You will be joining our team as a Data Scientist where you will be responsible for developing data-backed strategies for demand forecasting, price optimization, and demand elasticity modeling. Your key responsibilities will include: - Developing advanced time-series or machine learning models to predict demand at SKU, category, and regional levels by analyzing historical sales, seasonality, promotions, and market trends. - Building dynamic pricing models to determine optimal price points considering competitor analysis, elasticity, and inventory positions to enhance revenue and margins. - Analyzing the impact of price changes on consumer demand across segments using statistical techniques and machine learning. You will work closely with product, merchandising, finance, and marketing teams to incorporate insights into business decisions. Additionally, you will automate data pipelines, create dashboards for stakeholders to visualize forecasts and pricing scenarios, and conduct A/B testing and simulation modeling to validate forecasting and pricing strategies. To be successful in this role, you should have: - A Bachelor's or Master's degree in Data Science, Statistics, Economics, Applied Mathematics, or a related field. - At least 3 years of experience in retail analytics, pricing science, or demand forecasting. - Proficiency in Python/R, SQL, and relevant libraries such as Scikit-learn, Statsmodels, Prophet, and XGBoost. - Knowledge of econometrics, elasticity models, and optimization techniques. - Strong communication skills to convey complex insights to non-technical stakeholders. Preferred qualifications include experience in the fashion, footwear, or consumer goods industry, familiarity with supply chain and inventory dynamics in retail, and knowledge of reinforcement learning or revenue management frameworks.,