Engineering Data Scientist (Senior or Lead)
Tasks
- Align models to business goals and KPIs
- Architect scalable machine learning infrastructure
- Build production pipelines for data ingestion feature engineering model training deployment and monitoring
- Create decision support visualizations and reports
- Drive continuous improvement in machine learning tools and frameworks
- Ensure model governance explainability bias mitigation and compliance
- Establish best practices for model development testing versioning CI CD and reproducibility
- Implement security access controls and cost effective resource utilization
- Lead AI strategy and roadmap
- Manage data quality lineage and feature stores
- Mentor junior engineers through coaching and code reviews
- Monitor production models and deployments
- Provide technical leadership and set priorities for AI initiatives
- Translate requirements into technical solutions for analytics use cases
Perks/Benefits
- Disability insurance
- Flexible spending accounts
- Health insurance
- Health savings accounts
- Life insurance
- Paid time off
- Relocation
- Retirement savings plan
- Unpaid time off
Skills/Tech-stack
API Development | Azure | Bias Mitigation | CI/CD | Cloud Computing | Cloud platform | Data Engineering | Data Lineage | Data analytics | Databricks | ETL | Explainable AI | Feature Engineering | Feature Store | Google Cloud | Google Cloud Platform | Machine Learning | Model Deployment | Model Governance | Model Monitoring | Model Training | Teradata | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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