About SupplyWhy
SupplyWhy is building the future of autonomous supply chain planning. We deploy AI systems that replace fragile, spreadsheet-based processes with resilient, self-healing supply chains capable of making real-time decisions at enterprise scale. Starting with the automotive industry, we're tackling inefficiencies in one of the world's most complex supply chain ecosystems.
Our platform combines probabilistic forecasting, agentic AI, and deep supply chain domain expertise. We work with Fortune 500 manufacturers to transform how they plan, forecast, and respond to disruptions.

About the Role
As a Data Scientist on our Core ML team, you'll own and deliver key components of our forecasting and ML systems. This is hands-on technical work: time-series modeling, feature engineering, model productization, and MLOps. You'll work directly with the Lead DS to execute on our product roadmap for enterprise customers.
We're looking for someone who can operate independently - scoping work, making technical decisions, and delivering production-ready code with minimal oversight.



You'll also help mentor junior team members as we grow.

What You Will Do
Own end-to-end development of time-series forecasting models (statistical and ML-based) for demand prediction
Design and implement feature engineering pipelines for structured and unstructured data
Build anomaly detection systems for data quality and demand signal monitoring
Architect and deliver production-quality code: config-driven, testable, scalable Python modules
Implement model ensembling, hierarchical reconciliation, and automated model selection
Drive MLOps infrastructure: experiment tracking, CI/CD, model registry
Make technical decisions on model architecture, data pipelines, and system design
Mentor junior team members and contribute to technical standards
Collaborate with the team using AI-assisted development tools (Cursor, Claude Code)

Must Have
Bachelor's or Master's in Computer Science, Statistics, Mathem

📌 Data Scientist (India)
🏢 SupplyWhy.ai
📍 India