- Bengaluru, Karnataka, India
1–1 jobs· newest first
+10K new in the last hour
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