Hypersonix.ai is disrupting the e-commerce space with AI, ML and advanced decision capabilities to drive real-time business insights. Hypersonix.ai has been built ground up with new age technology to simplify the consumption of data for our customers in various industry verticals. We are looking for a hands-on Senior Data Scientist with strong expertise in traditional Machine Learning, retail analytics, pricing optimization, and demand forecasting. The ideal candidate will have experience working in Retail, CPG, or E-Commerce environments and will play a key role in designing and scaling ML-driven pricing and promotion solutions. 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. - Strong programming expertise in Python, including: - Pandas - NumPy - Object-Oriented Programming (OOP) - Scikit-learn - TensorFlow or similar ML frameworks - Experience working with PySpark and large-scale data processing systems. - Strong SQL skills and experience working with relational databases and data warehouses. - Experience developing APIs and ML services using Flask or similar frameworks. - 5+ years of experience in Retail, CPG, or E-Commerce domains with expertise in: - Demand forecasting - Price elasticity - Promotion optimization - Pricing strategy - Experience with MLOps platforms and deployment pipelines such as: - Databricks - Large Language Models (LLMs) - Google Vertex AI - Amazon SageMaker - Azure Machine Learning - Experience building and maintaining CI/CD pipelines for ML workflows.