Summer Intern Data Analyst

SUMA HARSHINI SAMANTHULA

Richardson, Texas, USA 469-***-**** adwolo@r.postjobfree.com LinkedIn

EDUCATION

University Of Texas at Dallas

Master of Science, Business Analytics, GPA: 3.92/4.0 May 2024 Relevant Coursework: Predictive Analytics, Big Data, Advance Statistics for Data Science, Cloud Computing Jawaharlal Nehru Technological University

Bachelor of Technology, Information Technology, GPA: 3.9/4.0 May 2020 Relevant Coursework: Operating Systems, Python Programming, Data Structures and Algorithms, Compiler Design TECHNICAL SKILLS

Statistical Analysis: Microsoft Excel, AB Testing, Hypothesis Testing Programming Language: Python, SAS, AWS Athena, Azure Databricks, R, Hadoop, Spark, Java, JavaScript Database Management System: PostgreSQL, Microsoft SQL Server (2019), MongoDB, SAP-ERP BI Tools: Tableau, Power BI, Alteryx ACHIEVEMENTS

• University gold medalist and title holder for the “Best outgoing student of B.Tech. Information Technology out of all affiliated colleges under JNTU” for the year 2019-2020. Honored to receive the medal from the governor of the State. PROFESSIONAL WORK EXPERIENCE

Micron Technology, Data Analyst Aug 2020 - Aug 2022

• Engaged in ModelN RC, a revenue and asset management tool, that supports the complicated business needs of Micron.

• Developed and maintained data pipelines and integrations between different systems, including Salesforce, SAP and ModelN RC, to ensure data consistency and accuracy across different platforms, and developed data validation procedures to detect and correct data errors.

• Worked on tools SQLDeveloperx64 and PuTTY to conduct data analysis and visualization using SQL, Python, and Tableau to identify trends and patterns in sales data, including revenue, bookings, and backlog resulting in a 25% increase in revenue and a 15% decrease in backlog.

• Designed and upheld forecasting models using statistical techniques such as time-series analysis, regression analysis, and data smoothing, and used these models to predict future sales trends and identify potential risks and opportunities. Likewise, collaborated with cross-functional teams, including Sales, Finance, and Operations, to develop pricing strategies and optimize deal pricing based on market trends and customer demand.

• Developed custom dashboards and reports using Tableau to visualize and communicate key performance metrics to stakeholders and contributed to the development of new analytical tools and processes to improve data quality, automate data analysis tasks, and optimize business processes resulting in a 15% increase in data analysis efficiency and a 10% decrease in data processing time. Brain O Vision, Summer Intern May 2019- Jun 2019

• Coordinated with the web development team to develop a responsive website using WordPress and conducted market research to identify target audience demographics, key performance metrics, and used this information to inform website design resulting in a 10% increase in website conversion rates.

• Implemented analytical tools, including Google Analytics and developed custom reports and dashboards to visualize the data. In addition, retained website functionality and eCommerce integration, using WordPress plugins and custom code resulting in a 10% increase in eCommerce conversion rates. PROJECTS

Loan Eligibility Prediction Project Dec 2022- Jan 2023

• Conducted data cleaning, data preprocessing, and data visualization on loan application records using Python, Pandas, and Matplotlib to identify data quality issues, outliers, and created quality control measures that enabled the correction of any data defects.

• Built and evaluated multiple predictive models using scikit-learn in Python to predict loan eligibility and evaluated model performance using various metrics such as accuracy, precision, recall, and F1-score.

• Used SQL to get insights on borrower behavior, loan characteristics, and repayment history and created interactive dashboards using Tableau to present the results of data analysis, including visualization of loan application trends, borrower demographics, and loan approval rates.

• Collaborated with the team to identify additional data sources that could enhance the predictive power of the model and used external data sources such as credit scores and socioeconomic data to improve the model's performance. Credit Card Customer Attrition Project Aug 2022- Dec 2022

• Performed the exploration and cleaning procedures of credit card customer details and executed data wrangling to prepare the data for analysis.

• Carried out feature engineering, including feature selection, feature scaling, and feature transformation, to identify the most important variables that contribute to customer attrition, and used this information to develop a more accurate and robust model.

• Performed EDA to identify relationships between customer behavior, demographic variables, and customer attrition and used this knowledge to improve the model's performance. Moreover, generated an ROC curve to understand the trade-off between true positive and false positive for binary classification.

• Implemented A/B testing and experimental design to test the impact of different customer retention strategies and developed recommendations for improving customer retention based on the results and provided recommendations for improving data quality and completeness. Calorie O meter Naïve Convolution Neural Network to predict the calorie intake in food Aug 2019-May 2020

● Developed a deep learning model using CNN to estimate the number of calories in food images, achieving an accuracy of 85% on a test dataset.

● Preprocessed food images using OpenCV to reduce noise and used data augmentation techniques to improve and increased model performance by 20%.

● Contributed to the development of open-source tools and libraries such as TensorFlow and Keras, to help advance the field of computer vision and deep learning and posted our entire analysis in the GitHub repository. LEADERSHIP AND ORGANIZATION EXPEREINCE

University of Texas at Dallas, Student Assistant Jan 2023 - Present

• Enforcing parking regulations on university property and adhering to policies, customer complaints were reduced by 25%.

• Led the department's customer service initiative with the greatest rate of client satisfaction. University of Texas at Dallas, Business Analytics Leadership Council, Student Mentor Sep 2022 - present

• Acted as a liaison between the class and the student government, representing the class's interests and concerns to the student administration and helped to organize and promote student events and activities, including fundraisers, community service projects, and social events.

• Stayed up to date on hiring needs, and used this information to help students prepare for interviews. Furthermore, exhibited strong organizational and management skills, including the ability to manage multiple tasks and projects, prioritize competing demands, and meet tight deadlines.

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