Data Scientist (R-19247)
Tasks
- Apply data observability and anomaly detection for detection and prioritization
- Build data quality measurement monitoring and remediation systems
- Coordinate agent workflows across systems
- Create agent interaction frameworks for rules metrics metadata lineage
- Design agentic AI systems for data quality
- Develop intelligent agents for data quality signal interpretation
- Document agent architectures behaviors and outcomes
- Ensure observability and auditability for risk and compliance
- Establish best practices for agent design evaluation and lifecycle
- Generate insights and recommendations from data quality signals
- Implement human in the loop governance workflows
- Integrate PowerBI and Looker dashboards for feedback
- Integrate large language models into data quality workflows
- Provide technical guidance and mentorship
- Support root cause analysis and decision making
- Use JIRA and Confluence for stakeholder communication
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic Systems | Anomaly Detection | Confluence | Data Lineage | Data Observability | Data Quality | Distributed Systems | GCP | Human-in-the-loop | Jira | Language Models | Large Language Models | Looker | Machine Learning | Metadata | PowerBI | Python | SQL | The Loop
Education
N/A
Roles
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