- Python
- Jupyter Notebook
- AWS
- Amazon Sagemaker
Role overview
Our client's platform helps automotive parts manufacturers and food & beverage companies improve their supply chain performance by more accurately predicting material lead times, labor utilization, inventory levels and future product demand. Their software as a Service (SaaS) improves forecasting results and business KPIs by applying the right external data modeling to counterbalance dynamic market conditions including Covid, seasonality, weather, socioeconomic & political impact patterns that affect SKU shortages and future buying behavior.
What you'll work on
- Supporting AI Engineering team on inference / production level outputs for existing supply chain projects
- Work in AWS with a client's historical time series data to fulfill AI modeling to align and update existing Jupyter code
- Build and maintain databases, as well as refactoring and optimizing existing code
- Experimenting with advanced tech to automate workflows and prepare for inference / production generation
- Brainstorming solutions to reduce ML errors / noise, increase accuracy, optimize model performance
- Building machine learning prediction models and using advanced frameworks / libraries
What we're looking for
Tags & focus areas
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