07 Nov
|
Blackbuck Insights
|
India
07 Nov
Blackbuck Insights
India
Job Information
- Job Type Full time
- Work Experience 7-10 years
- Industry IT Services
- Date Opened 10/27/2026
- City Bengaluru
- State/Province Karnataka
- Country India
- Zip/Postal Code 560045
About Us
BBI is a global data engineering consulting firm that empowers clients to effectively scale and modernize. We combine engineering fundamentals and innovative tools to execute business-critical, end-to-end projects on-time and on-budget. We offer expert services across Data Integration, Data Modernization, Data Migration, Data Architecture, Platform Support, and Application Services. Our goal is to provide business value in the most effective way for our clients so clients can focus on growth.
Job Description
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 (Excellent 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
📌 Data Governance Specialist (India)
🏢 Blackbuck Insights
📍 India