Experience

Third Estate Ventures

• United States
• Civic and Social Organizations
• 1 - 100 Employee

• Data Analyst

  • Oct 2023 - Present

  Buffalo, New York, United States • Working on the data manipulation lifecycle - extracting, preprocessing, cleaning data for analysis • Designing interactive dashboards and visualization as per business use case • Gathering insights on real estate and property data in various cities • Defining business metrics for ad-hoc analysis and reporting • Utilizing machine learning to identify trend elements from unstructured data



The Research Foundation for SUNY

• United States
• Education Management
• 700 & Above Employee

• Research Assistant

  • Jun 2023 - Oct 2023

  Buffalo, New York, United States ·Demonstrated expertise in using web scraping/crawling with libraries such as BeautifulSoup, Requests, and Scrapy to build a database of 1500 manufacturing companies in western New York by extracting relevant information from websites ·Skilled in data cleaning and organization, ensuring high-quality data. Applied preprocessing techniques to handle missing values, standardize formats, and remove duplicates. Stored cleaned data in CSV files for website integration



University at Buffalo

• United States
• Higher Education
• 700 & Above Employee

• Student

  • Aug 2022 - May 2023

  Buffalo, New York, United States



Matic Technology

• India
• IT Services and IT Consulting
• 1 - 100 Employee

• Business Analyst

  • Jun 2020 - May 2022

  Indore, Madhya Pradesh, India ·Gathered 1000 files, synthesized data, tracked progress, and followed up opportunities for operational and financial performance enhancements; generated actionable insights to provide best product experience to the customer ·Leveraged comprehensive gap analysis to define As-Is and To-Be processes, leading a large-scale project with streamlined implementations, targeted training, and achieving an impressive 30% increase in team efficiency ·Conducted thorough review, implemented new… Show more ·Gathered 1000 files, synthesized data, tracked progress, and followed up opportunities for operational and financial performance enhancements; generated actionable insights to provide best product experience to the customer ·Leveraged comprehensive gap analysis to define As-Is and To-Be processes, leading a large-scale project with streamlined implementations, targeted training, and achieving an impressive 30% increase in team efficiency ·Conducted thorough review, implemented new framework, reducing company's financial threat exposure by an impressive 45% through enhanced risk management policies and effective mitigation support ·Actively participated in Agile ceremonies, utilizing Jira for efficient communication, collaboration, and team alignment during sprint planning, stand-ups, retrospectives, ensuring smooth project execution and effective decision-making

• Data Analyst

  • Oct 2017 - May 2020

  Indore, Madhya Pradesh, India ·Proactively addressed 50+ ad hoc queries within 24 hours; achieved a remarkable 90% resolution rate on first contact, minimizing follow-up requirements and enhancing client satisfaction by 25% ·Developed and maintained efficient SQL scripts for data cleaning, transformation, and integration, resulting in streamlined data processing and reporting workflows, improving overall data accuracy and timeliness ·Performed collection, pre-processing and cleaning on structured and unstructured data… Show more ·Proactively addressed 50+ ad hoc queries within 24 hours; achieved a remarkable 90% resolution rate on first contact, minimizing follow-up requirements and enhancing client satisfaction by 25% ·Developed and maintained efficient SQL scripts for data cleaning, transformation, and integration, resulting in streamlined data processing and reporting workflows, improving overall data accuracy and timeliness ·Performed collection, pre-processing and cleaning on structured and unstructured data and created a detailed modeling and analysis report of the data used by various business initiatives that led to increased annual savings by 20% ·By analyzing data from 10,000 active users, our cross-functional teams successfully achieved key performance indicators (KPIs), resulting in 33% boost in average app engagement time and a significant 15% reduction in drop-off rate ·Tech Stack: Machine Learning Frameworks , supervised learning (Linear and Logistic Regression, k-NN, Decision tree, Random Forest, XG Boost, Neural network), unsupervised learning (clustering, K-means)