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.

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