Open to opportunities

Tejaswini Waghmare

@tejaswiniwaghmare

Message

I build production ML, ETL pipelines, and executive BI dashboards as a Data Analyst & Data Science professional.

United States

Message

What I'm looking for

I’m looking for a role where I can ship production-ready ML/LLM systems, own ETL data reliability, and deliver BI dashboards that help business teams decide faster—using AWS/GCP and clean, well-documented engineering.

I’m an M.S. Data Science & Analytics candidate with hands-on experience delivering production ML models, ETL pipelines, and executive BI dashboards for Fortune 500 financial institutions. I use SQL and Python for EDA, A/B testing, anomaly detection, and customer insights—and I focus on turning complex data into business action for non-technical stakeholders.

In my recent roles, I designed LLM-assisted workflows and automated ETL data cleaning pipelines, and I built Tableau dashboards that reduced manual reporting effort by ~40%. I also architected an agentic RAG system on Amazon Bedrock (cutting document search time 60–75%), enabled sub-0.2s search latency across 100+ files, and added guardrails blocking 75–90% of unsafe responses—so models stay trustworthy and measurable.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst (Research Assistant)

Current

FanDuel

Jan 2026 - Present (6 months)

Designed and evaluated LLM-assisted workflows for sports and user behavior research, building feedback loops to assess model output quality. Built Python/SQL ETL cleaning pipelines and Tableau dashboards, reducing manual reporting effort by ~40%.

ETL Python Pandas NumPy SQL Classification regression Clustering Customer Analytics Tableau A B Testing Research Analytics Data Validation

Data Engineer (Research Assistant)

Truist Bank

Aug 2025 - Dec 2025 (4 months)

Architected a production-grade agentic RAG system on Amazon Bedrock with LLM orchestration across retrieval, analysis, and generation tools. Implemented an NLP ingestion pipeline with NLTK and OpenSearch embeddings, added output guardrails, and improved document search time by 60–75%.

Agentic RAG Orchestration Docker NLTK OpenSearch Embeddings GuardRails OpenTelemetry NLP Document Ingestion Production ML Systems

Data Science Consultant

Infosys

Sep 2024 - Jul 2025 (10 months)

Built customer churn prediction models (logistic regression, random forest) on a 300K+ row dataset achieving 98% accuracy. Performed A/B testing and SQL/Python transaction analysis, and delivered Tableau dashboards and executive reports to business stakeholders.

Churn Modeling Logistic Regression Random Forest A B Testing Python Tableau Executive Reporting Data Analysis

Data & Analytics Engineer

Capgemini

Oct 2021 - Sep 2024 (2 years 11 months)

Built and maintained GCP data pipelines (BigQuery, Data Prep, Data Fusion) for financial data infrastructure, achieving 98% accurate record segregation. Developed 25+ Tableau and Power BI dashboards for payment flow KPIs and applied Python-based statistical analysis and anomaly detection to reduce incident rates.

GCP BigQuery Python Pandas NumPy Scipy Statistical Analysis Anomaly Detection Tableau Power BI Data Pipelines KPIs

Education

Degrees, certifications, and relevant coursework

Georgia State University

Master of Science, Data Science and Analytics

2025 -

M.S. candidate in Data Science and Analytics, applying hands-on skills in production ML models, ETL pipelines, and executive BI dashboards. Built and shipped an Amazon Bedrock AI system in production and uses SQL/Python for EDA, A/B testing, anomaly detection, and customer insights.