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Data Governance Specialist

BB Insights · Bengaluru, Karnataka, India

Strong hiring record · median 7 days open

100100

Hiring signal

Actively hiring

Still listed on the employer's own board · How we score

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  • Still listed on the employer's own board

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Technical Skills & Technologies

Languages & Query

  • SQL- data profiling, validation rules, quality checks, large-scale dataset analysis
  • Python - automation, ML/AI techniques, scripting, pipeline development

Data Quality & Governance

  • Data quality frameworks (Great Expectations, dbt tests) augmented with ML/LLM
  • Data governance practices (metadata management, lineage review, issue tracking)
  • Data stewardship, remediation workflows, and automated quality monitoring pipelines
  • Data lineage and impact analysis
  • Data completeness and reliability measurement

ML/AI for Data Quality

  • Supervised learning - classification models to flag bad records (e.g., mislabeled diagnosis codes, incorrect attributions)
  • Unsupervised learning - clustering to detect outliers, unusual patterns, and grouping anomalies in clinical data
  • Anomaly detection - model-driven (Isolation Forest, LOF, One-Class SVM)
  • Data drift monitoring - statistical process control (KS test, PSI, Jensen-Shannon divergence)
  • NLP / Text Analytics - parsing unstructured clinical notes, extracting entities, detecting coding inconsistencies
  • Record linkage / Entity resolution - ML-based deduplication using probabilistic matching (e.g., patient matching across systems)
  • Pattern recognition and root cause analysis

AI Frameworks & Libraries

  • scikit-learn - anomaly detection, clustering, classification
  • PyOD - outlier detection
  • TensorFlow / PyTorch - deep learning for complex pattern recognition in large clinical datasets
  • LLMs (GPT, Claude, etc.) - automated root cause summarization, natural language quality reports, code review assistance

Dash boarding & Reporting

  • Alerting and monitoring dashboards (Tableau, Power BI, Streamlit, or similar)
  • Data quality trend reporting and operational risk communication

Healthcare Domain Knowledge

  • Healthcare coding systems (ICD, CPT, HCPCS)
  • Member attribution logic
  • Clinical quality measures (HEDIS, Stars)
  • Interoperability data (HL7, FHIR)
  • Payer/provider/clinical/population health datasets

Skills

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