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Vardhan Are
Mid-level Data Analyst specializing in AWS-based ETL, churn analytics, and BI dashboards
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Data/ML practitioner with experience at Airtel and Lincoln Financial delivering measurable business outcomes: improved retention 15% via NLP sentiment analysis and cut response time ~25% using sentence-BERT + FAISS semantic linking. Strong in data quality/identity resolution (SQL + fuzzy matching) and in building production-grade Python workflows orchestrated with Airflow/AWS Glue, including validation and dashboard integration in Power BI.
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Key Strengths
- Applied NLP sentiment analysis on large-scale customer feedback; improved customer retention by 15%
- Automated large-volume text preprocessing (NLTK/regex) with batching for efficient processing
- Entity resolution across systems using SQL + fuzzy matching; achieved 95%+ resolved records via thresholds and manual review
- Built semantic search/data linking with sentence-BERT + FAISS; reduced response time ~25%
- Production-minded Python data workflows with orchestration (Airflow/AWS Glue), validation checks, and Git-based versioning
- Balanced experimentation and delivery; shipped churn model (logistic regression) to production with Power BI integration after 85%+ accuracy
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