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Pooja Dhanaji Bodke
Junior Data Analyst specializing in BI, analytics, and machine learning
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About
Analytics professional with hands-on experience turning messy Excel-based operational data into SQL/Python pipelines and Power BI dashboards, including a production bottleneck project that improved workflow efficiency by 20%. Also brings applied machine learning experience from a Databricks/PySpark loan risk scoring project using logistic regression and XGBoost on large-scale S3 data.
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Key Strengths
- Built SQL pipelines to clean messy operational Excel data into analysis-ready tables
- Strong data quality remediation using standardization lookups, deduplication, and validation rules
- Designed reporting-friendly data models with fact/dimension tables
- Validated analytics outputs by reconciling source aggregates and confirming KPIs with stakeholders
- Improved reporting performance with indexing and pre-aggregated tables
- Built reproducible Python analytics workflows spanning ingestion, analysis, modeling, and dashboard delivery
- Experience combining SQL, Python, and Power BI for end-to-end analytics delivery
- Owned production bottleneck analytics from metric definition to stakeholder rollout
- Drove operational improvement through machine/shift segmentation analysis
- Delivered measurable impact: 20% increase in workflow efficiency
- Built large-scale loan default risk scoring pipeline in PySpark/Databricks on S3 data
- Handled ML edge cases including missing values, duplicate records, imbalanced classes, and cold-start customers
- Translated predictive model outputs into stakeholder-friendly risk categories and dashboards
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