Data Scientist
Tasks
- Apply manufacturing analytics for root cause and scrap reduction
- Build reusable machine learning AI statistical models
- Collaborate with product and engineering leaders
- Define analytic needs and ensure data capture
- Develop dashboards with PowerBi
- Develop machine learning AI algorithms
- Develop models for sales recommendations and segmentation
- Develop models for supply chain analytics
- Identify business opportunities from data
- Mine and analyze data
- Provide technical direction to team members
- Translate insights into actionable recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Agentic RAG | Amazon Web Services | Anomaly Detection | Artificial Intelligence | Azure | CI/CD | Cause analysis | Chain-of-Thought | Classification | Clustering | Computer Vision | Customer Segmentation | Data Cleansing | Data Exploration | Data Imputation | Data Preprocessing | Data Transformation | Decision Tree | Deep learning | Demand forecasting | Django | Docker | Feature Selection | Flask | Forecasting | Graph RAG | Inventory optimization | K-Means | K-Nearest Neighbors | K-nearest | Langchain | Machine Learning | Multivariate Regression | Nearest neighbors | Neural Networks | Outlier Detection | PowerBI | Price elasticity | Python | RAG | Random Forest | Recommendation Systems | Root Cause Analysis | Root cause | Segmentation | Supply Chain | Supply Chain Analytics | Support Vector Machine | Tree of Thought | Uncertainty Analysis | Web Services
Education
Roles
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