Data Platform & Forecasting Backend
Budget: €750 – €1,500 EUR
We’re building a retail analytics SaaS.
The React analytics dashboards are already built — we now need help standardizing and scaling the backend data & ML layer.
What you’ll do:
Build a robust Python backend for multi-tenant retail data
Design ingestion pipelines for Excel + partner APIs
Standardize and normalize client data (dates, units, currencies)
Design a per-client database schema
Implement production-ready models for:
Demand forecasting
Inventory planning
Price optimization
Expose models via REST APIs
Power analytics dashboards via clean data endpoints (no frontend work)
Add monitoring for model accuracy, drift, and latency
Prepare everything for Docker / Kubernetes
Requirements:
Strong Python, data engineering, and ML deployment experience
Time-series / forecasting experience
Pragmatic, production-focused mindset
Success looks like:
New client data ingests end-to-end in <10 minutes
Forecast MAPE <10%
Inventory recommendations within ±5% of stockouts
Price optimization shows ≥3% simulated margin lift
If this fits your experience, let’s start.
The React analytics dashboards are already built — we now need help standardizing and scaling the backend data & ML layer.
What you’ll do:
Build a robust Python backend for multi-tenant retail data
Design ingestion pipelines for Excel + partner APIs
Standardize and normalize client data (dates, units, currencies)
Design a per-client database schema
Implement production-ready models for:
Demand forecasting
Inventory planning
Price optimization
Expose models via REST APIs
Power analytics dashboards via clean data endpoints (no frontend work)
Add monitoring for model accuracy, drift, and latency
Prepare everything for Docker / Kubernetes
Requirements:
Strong Python, data engineering, and ML deployment experience
Time-series / forecasting experience
Pragmatic, production-focused mindset
Success looks like:
New client data ingests end-to-end in <10 minutes
Forecast MAPE <10%
Inventory recommendations within ±5% of stockouts
Price optimization shows ≥3% simulated margin lift
If this fits your experience, let’s start.