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.