Summary
Overview
Work History
Education
Skills
Academic Project Experience
Academic Project Experience
Timeline
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NIKHIL KUSUMANCHI

NIKHIL KUSUMANCHI

Summary

Results-driven Data Analyst at ADP with experience in data extraction, transformation, and integration for client data migration. Proficient in Python and SQL, with expertise in Snowflake and Apache Airflow for efficient data processing. Skilled in data analysis, regression analysis, and business analytics using PowerBI. Experienced in collaborating with cross-functional teams to define metrics and resolve complex data challenges.

Overview

2
2
years of professional experience

Work History

Data Analyst(Member Technical)

ADP
Hyderabad
03.2021 - 08.2023
  • Extracted and transformed client data from multiple ERP systems using Python and SQL to ensure accuracy and integrity for payroll systems. Identified and resolved inconsistencies, standardized formatting, and delivered clean datasets for seamless integration into ADP. Also supported enterprise pricing management and rate adjustment processes.
  • Automated laborious, manual Excel-based processes using Pandas and Apache Airflow for data analysis. This effort reduced the manual workload by 40% and increased accuracy in data analysis.
  • Applied advanced statistical methods (Z-tests, t-tests, ANOVA, Chi-square) and regularized regression models in Python (Pandas, SciPy, Statsmodels, scikit-learn) on large-scale employee datasets integrating tenure, performance ratings, role scarcity, and market benchmarks to forecast merit-based salary-hike recommendations with 30% higher accuracy.
  • Engineered, end-to-end ETL pipeline that extracted high-volume transactional data from SAP HANA via advanced SQL scripting, staged it in Amazon S3, ingested it into Snowflake through Snowpipe, applied scalable transformations, and reconciled Snowflake tables with source-system records using Power BI for data-quality ensuring accurate, near-real-time data availability for enterprise analytics and reporting.
  • Designed and implemented dashboards and reports in Power BI to track key organizational metrics such as employee performance, efficiency trends, financial summaries, supported process improvement and cost-reduction strategies.
  • Mentored a 14-member team on data quality assurance and data extractions, facilitating successful data migration and transformation projects. Recognized 12 times for performance excellence and problem-solving initiative.
  • Delivered strategic insights to C-level leadership to guide, enabling key business processes to support informed decision-making

Education

Master of Science - Information Science

University of North Texas
Denton, TX
05-2025

Skills

  • Programming languages: Python, SQL, HTML/CSS
  • Tools: Snowflake, Power BI, RDBMS, Apache Airflow, AWS, Excel, Google Sheets
  • Skills: Statistical Data Analysis, Data Cleaning, Data Analysis, Data visualization, Data Engineering, Data Warehousing, web scraping, Machine Learning, Applied AI

Academic Project Experience

Sentimental Analysis and Recommendation system of Swiggy Restaurants:

  • Built a multithreaded Python scraper (Requests / BeautifulSoup/ Selenium) that harvested 15 K Swiggy restaurant profiles and 200 K customer reviews, exporting raw CSV files for repeatable loads.
  • Normalized cuisine, location, and pricing attributes, token-cleaned and lemmatized review text with Pandas and NLTK, producing analytics-ready tables for NLP and recommendations.
  • Employed NRCLex to generate polarity, emotion scores and ran T-tests & ANOVA to surface statistically significant satisfaction leaders, revealing a 12% sentiment gap between top and mid-tier outlets.
  • Designed a content-based recommender that encodes cuisine and locality vectors and applies cosine similarity, delivering top-10 restaurant suggestions

Academic Project Experience

End-to-End Automated Real Estate Data Pipeline:

  • Created a Python-Selenium webscraper, scheduled via Apache Airflow, that harvests nearly 10 K new property listings per day from “99acres.com”.
  • Landed raw files in AWS S3 and streamed them into Snowflake with Snowpipe, layering RAW → STG → DM tables for scalable analysis.
  • Applied SQL, Streams, and Tasks to cleanse data, achieving >99% data-quality compliance for analytics.
  • Integrated Snowflake to Power BI, built DAX-driven dashboards that surface real-time price trends and cut manual reporting effort by 80%.

Timeline

Data Analyst(Member Technical)

ADP
03.2021 - 08.2023

Master of Science - Information Science

University of North Texas

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