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Click here or scroll down to respond to this candidateCandidate's Name
Data Analyst SQL, Python, Tableau, Power BI, Machine Learning, Statistical AnalysisPHONE NUMBER AVAILABLE EMAIL AVAILABLE LINKEDIN LINK AVAILABLE 5 YOE in Fintech & Analytics Analyzing Business Processes Led Agile Teams End-to-end Data Analysis EDUCATIONSyracuse University, School of Information Studies New York Master of Science in Data Science (CGPA: 3.9 / 4.0) December Street Address
Teaching Assistant - Mentored 120 students in enhancing their data analytics skills for informed business decision-making Gujarat Technological University IndiaBachelor of Engineering in Computer Science and Engineering (CGPA: 3.98 / 4.0) May 2018 Published and presented a research paper on Data Migration Types and Challenges in an international journal PROFESSIONAL EXPERIENCEBusiness Data Analyst Syracuse University New York June 2022 Jan 2023 Facilitated meetings with stakeholders to gather requirements, clarify objectives, and ensure alignment on project deliverables. Executed complex SQL queries to gather data from different sources for analytics using Databricks, improving accessibility by 20%. Pioneered Tableau-based reporting, slashing report time by 90% and boosting user engagement 80%. Automated data fetching, aggregation, and report generation using Python and VBA macros, saving 10 hours/week of manual labor Served as a Subject Matter Expert (SME) to senior stakeholders and other team members, offering insights and guidance in the development of an interactive reporting system using Tableau Senior Business Data Analyst DSPL Feb 2021 Dec 2021 Analyzed e-commerce pharma platform with SWOT, benchmarking, use cases to streamline operations resulting in 25% improvement Collaborated with cross-functional agile teams (BA, Developers & QA) to refine and prioritize EPICs and user stories in JIRA Developed and maintained an analytics pipeline with Databricks, and Power BI for real-time KPI tracking and data-driven decisions. Utilized statistical analysis and Power BI to identify bottlenecks, increasing order fulfillment efficiency by 15% and gaining stakeholder approval through visualizations. Created and validated statistical models in Python for business challenges, integrating insights into Power BI dashboards for applications like risk forecasting, customer churn prediction, targeted marketing, and supply chain optimization. Senior Data Analyst AtliQ Technologies July 2019 Jan 2021 Increased sales productivity by 25% through Salesforce CRM implementation via stakeholder interviews and workflow automation. Led 10-person team on critical retail project, ensuring on-time, budget-conscious delivery. Reduced delays by 20% and saved $5,000 with contingency plans. Designed ETL processes to handle various file formats (XML, JSON, CSV, Excel), increasing data processing efficiency by 35%. Designed a data model for customer purchase history, cutting data retrieval time by 70% and increasing analysis efficiency by 35%. Automated performance dashboards and reports using Python, SQL, and Tableau, delivering actionable insights for operational and marketing improvements.Business Data Analyst Desai Tech Solutions June 2018 June 2019 Supported timely and successful project delivery of a project by assisting with project planning, monitoring, and tracking progress Facilitated scrum ceremonies (Planning, Release, Reviews, & Retrospectives) enhancing team collaboration & productivity. Achieved a 20% increase in data processing efficiency by developing an automated workflow integrating SPSS with SQL databases, enabling faster and more accurate reporting for quarterly business reviews. Utilized advanced statistical techniques and data visualization tools such as R and Excel to transform raw data into actionable business strategies, which enhanced revenue by 10%. Analyzed marketing data using SQL and Python for the platform, leading to a 20% increase in customer retention by identifying key consumer behavior patterns and implementing targeted marketing strategies. Developed and presented data-driven insights using Tableau to senior management, resulting in a 15% boost in conversion rates through the optimization of the user acquisition funnel. Business Insights Analyst Allianz Cloud Pvt Ltd. June 2017 May 2018 Optimized asset allocation strategies through data analysis and predictive modeling, increasing portfolio returns by 20%. Led cross-functional teams to develop Tableau dashboards & reports, streamlining reporting by 30% and providing actionable insights Increased data accessibility by designing and implementing a comprehensive database management system, ensuring seamless integration with SPSS for real-time analytics and reporting. Enhanced marketing campaigns by 15% through A/B testing with Google Analytics and Python, presenting findings to senior management. Boosted platform adoption by 20% using machine learning in Python to predict customer preferences and share insights with teams. TECHNICAL SKILLSProgramming Languages: Python, SQL (MySQL, PostgreSQL, MSSQL), SPSS, MS Access, Java, R, Tableau, Power BI Cloud: Virtualization, Aws (S3, Athena, RDS, Lambda, EC2, SNS), Azure (AutoML, Databricks), Google Cloud Platform (GCP) Certifications: Tableau Desktop Specialist, Certified ScrumMaster (CSM), Certified Capability in Business Analysis (CCBA) ACADEMIC PROJECTSBig Data Analytics Project Text Mining and Classification Jan 2023 May 2023 Built LSTM, Logistic Regression, Nave Bayes, and SVM using PySpark and Hadoop for hate speech detection and toxic comment classification Machine Learning Project Data Mining and Recommendation System Aug 2022 Dec 2022 Used KNN, SVM, Decision Trees, Gradient Boost, Random Forest in Python, and Tableau to predict the major factors affecting the selection in the H1b lottery, achieving an accuracy of 90%. Implemented the interactive recommendation system using flask Financial Analytics Project Capital Asset Pricing Model (CAPM) Aug 2022 Dec 2022 Used Python to investigate the Capital Asset Pricing model and compute beta exposure market by collecting data from various sources, including databases, APIs, and web scraping, performing data pre-processing and finally running a linear regression model |
