Deep Learning Data Analysis

VASAVI VEERLA

+1-443-***-**** ****************@*****.*** linkedin.com/in/vasaviveerla/

EDUCATION

MS in Data Science, University of Maryland, Baltimore County

MBA in Business Analytics, University of Hyderabad

SKILLS

•Programming Languages: Python, R

•Visualization Tools: Power BI, Tableau, Advanced Excel, Pivot tables, Flask, Plotly

•ML Frameworks and libraries: TensorFlow, NLP, Deep Learning, Artificial Intelligence

•Database skills: SQL, SAP, Oracle, NoSQL, T-SQL, MongoDB

•Tools: Alteryx, Azure, Hadoop, GitHub, Microsoft Office 365

EXPERIENCE

Programmer Analyst May 2021 - Aug 2022

Cognizant Hyderabad, India

•Developed complex SQL queries using MySQL and Data Analysis Expression Language (DAX), utilized Ad- vanced Excel for data analysis. Streamlined the process, reducing the time required from 1 month to 15 days.

•Responsible for migrating 6 Power BI reports to other environments, managing monthly and quarterly loads for 6 applications, participating in requirement meetings and data mapping sessions, and demonstrating basic knowledge of Azure Analytics Services and ADF components.

•Managed Power BI on-prem data gateway, workspaces. Implemented security measures, error monitoring, report publishing, and providing training to business users on Power BI utilization.

•Expertly leveraged a wide range of Azure cloud platform analytical tools, such as Azure Data Lake Store (ADLS), Azure Data Factory (ADF), and Azure Data Bricks (ADB), to effectively process and analyze massive datasets. Successfully processed and analyzed over 1 terabyte of data, optimizing performance and delivering actionable insights for informed decision-making.

•Translated technical findings into business insights, facilitating more strategic and data-driven decisions.

Business Intelligence Analyst Dec 2019 - April 2021

CommScope Hyderabad, India

•Employed SAP BODS ETL tools to design, develop, and implement over 30 ETL processes, guaranteeing exceptional data accuracy and completeness throughout the procurement process

•Spearheaded the collaboration with business users to gather document supply chain management analytics requirements, leveraging Tableau and SQL to construct stored Procedures for a robust data and reporting infrastructure from the ground up. This initiative resulted in a 20% increase in on-time delivery performance.

•With a keen eye for detail and a passion for productivity, I efficiently tackled tasks and accomplish goals while working on Microsoft Office 365, contributing to a seamless and successful digital experience.

•Established KPIs to measure procurement-related business decisions, leading to a 15% reduction in procure- ment cycle time. Collaborated with cross-functional teams to ensure consistent data collection and analysis methodologies, resulting in a 30% improvement in data accuracy.

•Worked as technical expertise and business acumen to bridge the gap between technology and business objectives, leading to a 25% increase in project alignment with strategic goals.

Jr Associate July 2016 - Nov 2019

Addpure Labs Hyderabad, India

•Collaborated extensively with sales operations and product analytics teams, adeptly preparing over 50 KPI reports using Tableau.

•Automated reporting processes, resulting in a remarkable 40% reduction in SLA time.Advanced analytical techniques in Excel and Tableau to deliver data-driven insights and drive business growth.

•Demonstrated strong business analyst skills by providing actionable recommendations based on data analysis, leading to a 10% improvement in cross-selling effectiveness.

•Actively engaged in more than 20 data-driven discussions with cross-functional teams, aiding in the formulation of effective business strategies

PROJECTS

Analyzing the Liquor Sales at IOWA

•Led end-to-end analysis of liquor sales data for Iowa, managing a dataset of 1M+ records. Performed data cleansing, transformation, and exploratory data analysis to extract valuable insights.

•Implemented advanced statistical models and applied forecasting techniques to predict future liquor sales with an impressive accuracy rate of over 82%, enabling data-driven demand forecasting and optimizing inventory management.

•Presented actionable findings and strategic recommendations to liquor shop owners, including optimized stock management strategies, identifying lucrative opportunities to establish new stores in specific areas, and highlight- ing the highest-selling items that have the potential to boost sales by a minimum of 10%.achieved an accuracy rate of over 82% in predicting customer churn.

Big Data Film Analytics - Unveiling Insights and Trends in the Movie Industry

•Performed in-depth analysis of movie data utilizing MongoDB and harnessing the capabilities of Spark for stream- lined processing of a substantial dataset consisting of 26 million rows.

•Developed a robust database infrastructure to store and manage the massive movie dataset, ensuring scalability and real-time access to information. MongoDB acted as the primary database for efficient storage and retrieval of movie-related data.

•Employed Tableau for immersive data visualization, creating interactive dashboards and visual representations to communicate key findings effectively. Presented captivating visualizations of most liked movie genre,Top 10

directors and actors, IMDB performance.

Predictive machine learning algorithms

•Constructed a highly accurate predictive model for customer churn utilizing machine learning algorithms like Logistic Regression and Random Forest in Python.

•Conducted extensive data analysis and feature engineering to identify factors influencing customer churn.

•Achieved an accuracy rate of over 85% in predicting customer churn, providing valuable insights to inform targeted retention strategies and improve customer satisfaction.

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