Sr. Data Scientist
Tasks
- Analyze usage performance and outcome data for agentic AI features
- Build and validate machine learning models and agentic workflows
- Build dashboards to track agent performance and business impact
- Collaborate with engineering to productionize models and monitor post launch
- Define and maintain eval suites and benchmarks for agent safety and reliability
- Define success metrics and ensure statistical rigor
- Design and run A B tests and offline evaluations
- Develop regression frameworks and test case libraries for model and prompt updates
- Isolate AI driven impact and report ROI to stakeholders
Perks/Benefits
- Employee assistance program
- Free financial counseling
- Health coaching
- Hybrid work schedule
- Leadership development
- PTO
- Parental leave
- Tuition assistance program
- Virtual training opportunities
- Workplace productivity and technology tools and training
Skills/Tech-stack
A/B | A/B Testing | AWS Bedrock | Agent systems | Azure OpenAI | B testing | Causal Inference | Dashboarding | Data Visualization | Evaluation Frameworks | Experiment design | Google Vertex | Google Vertex AI | LLM Agents | Langsmith | Language Models | Language Processing | Large Language Models | Machine Learning | Model Evaluation | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Observability | Prompt engineering | Python | Ragas | Regression testing | SQL | Statistical Analysis | Vertex AI | Weights and Biases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Regions
Countries
States
Cities
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