Data Scientist_ML

Roles and Responsibilities 

• Lead the design, development, and deployment of scalable machine learning solutions focused on pricing optimization, demand forecasting, and promotion planning.  

• Build and improve statistical and machine learning models for:  

- Demand forecasting  

- Price elasticity modeling  

- Promotion optimization  

- Inventory and revenue forecasting  

• Design, build and deploy robust ML pipelines in Databricks, build model monitoring systems, and production-ready APIs.  

• Ability to design and evaluate transformer-based time series forecasting models for large-scale retail sales forecasting and demand planning. 

• Drive experimentation, model evaluation, and continuous improvement of forecasting and pricing models. 

• Analyze large-scale structured and unstructured retail datasets to uncover trends, customer behavior patterns, and pricing insights.  

• Develop data-driven strategies that help maximize revenue, profitability, and pricing efficiency across products and categories.  

• Apply advanced statistical techniques and machine learning algorithms to solve complex retail business problems.  

• Collaborate closely with Product, Engineering, Data Engineering, and Business teams to translate business requirements into scalable ML solutions.  

• Mentor junior data scientists and provide technical guidance across cross-functional teams.  

• Communicate analytical findings and business recommendations clearly to both technical and non-technical stakeholders. 

Requirements 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.  

• 5+ years of hands-on experience in Machine Learning and Data Science.  

• Strong background in mathematics, probability, statistics, and regression analysis.  

• Solid understanding of traditional machine learning algorithms and statistical modeling techniques.