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Nandini Sinha

@nandinisinha

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Data Analyst at Havells India Ltd. who prevented $430K in operational losses with automated anomaly detection models.

United States

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At Havells India Ltd., I analyzed operational data using Python, SQL, and PySpark to support decisions across marketing, operations, and finance. I built automated anomaly detection models that identified data quality issues and supply chain irregularities, preventing $430K in operational losses.

At Labwork Flows LLC, I analyzed event data and created Python workflows for data validation and cleansing, reducing reporting latency by 35% and eliminating 95% of data quality issues before analysis. My projects include interactive sales dashboards that improved quarterly sales targeting by 15% and churn models that achieved 93% accuracy.

Experience

Work history, roles, and key accomplishments

Data Analyst Intern

Labwork Flows LLC

Jun 2026 - Aug 2026 (2 months)

Analyzed large-scale event datasets using Python and SQL to identify user behavior patterns and trends, generating actionable insights that reduced reporting latency by 35%. Designed automated data validation and cleansing workflows in Python, ensuring data integrity across reporting systems and eliminating 95% of data quality issues prior to analysis.

Python SQL Data Analysis Data Validation Data Cleaning Automation

Data Analyst

Havells India Ltd.

Feb 2023 - May 2025 (2 years 3 months)

Collected, cleaned, and analyzed 500GB+ of daily operational data using Python, SQL, and PySpark to identify trends, patterns, and correlations supporting strategic decisions across marketing, operations, and finance. Created and maintained interactive Power BI dashboards using advanced SQL aggregations and window functions, presenting key metrics to supply chain stakeholders and improving operati

Python SQL PySpark Power BI Data Analysis Data Cleaning Statistical Analysis Anomaly Detection Dashboarding

Data Analyst Trainee

Havells India Ltd.

Jul 2022 - Feb 2023 (7 months)

Developed automated SQL queries and Python scripts to extract, clean, and validate raw operational data from multiple databases, improving daily reporting reliability by 30%. Collaborated with cross-functional teams including marketing, operations, and finance to understand departmental data needs, documenting analytical requirements and enforcing data quality standards.

SQL Python Data Extraction Data Cleaning Data Validation Collaboration Documentation

Education

Degrees, certifications, and relevant coursework

University of Maryland, Robert H. Smith School of Business

Master of Science, Information Systems

Pursuing a Master of Science in Information Systems with coursework in data analytics, business intelligence, machine learning, and statistical modeling.