Business Analyst Intelligence

NITHYA VAIDYANATH

Round Rock, TX – ***** ***********************@*****.*** 979-***-**** https://www.linkedin.com/in/nithyashree-vaidyanath-47b148184/ https://nithyaportfolio.super.site/

PROFESSIONAL SUMMARY

Results-driven Business Analyst & Data Specialist with a master’s in business Analytics, skilled in data visualization, predictive modeling, and cloud computing. Adept at translating complex business requirements into scalable solutions using Python, SQL, AWS, and Tableau. Proven expertise in stakeholder collaboration, process optimization, and business intelligence.

EDUCATION

Master of Science in Business Analytics, East Texas A&M University Aug 2023 - Dec 2024

Dallas, TX, USA GPA: 4/4

Coursework: Project Management, CRM, Python for BA, Applied Decision Modelling, Data warehousing, BA for Managers, BI

Bachelor of Technology in Information Science Engineering, The National Institute of Engineering Jul 2016 - Jun 2020

Mysore, KA, India GPA:3.5/4

Coursework: Database Management, Machine Learning, Artificial Intelligence, Object Oriented programming, Software Engineering

SKILLS

• Programming Languages: Python, Java, R Programming, C++, C. • Database: PostgreSQL, MySQL

• Tools and Technologies: Microsoft Office, Advanced MS Excel (VLOOKUP, Pivot tables, and Macros), Data Visualization Tools (Power BI,

Tableau), GitHub, Git, PowerPoints, Jira, Kanban, Azure DevOps, AWS, Visio.

• Data & Analytics: Data-driven decision-making, ETL pipelines, KPI analysis, Process automation, Data storytelling, Predictive modeling

CERTIFICATIONS

• Google Business Intelligence • Product Management: An Introduction - IBM

• Google Foundations of Project Management • Professional Scrum Master 1 - Scrum.org

• AZ-900 - Microsoft Azure Fundamentals from Microsoft.

PROFESSIONAL EXPERIENCE

Quality Assurance Analyst Mercedes-Benz Research and Development, Bengaluru, India Oct 2020 – Sep 2022

• Collaborated with the QA Team Lead and stakeholders to define KPIs, test plans, and objectives, ensuring the software met all business

requirements, leading to a noticeable reduction in post-release defects and improved software performance.

• Led UI testing for the Onboard Logic Unit (OLU), automating 100+ manual test cases using Java, Appium, and Cucumber, optimizing testing

processes, increasing efficiency, and tracking progress while resolving issues using Jira to ensure alignment with business goals

• Identified and resolved 50+ critical defects prior to production, significantly improving software reliability, minimizing defect leakage, and

keeping stakeholders informed through clear bug status reports and scorecards.

• Managed bi-weekly sprints, facilitated backlog grooming, and ensured timely issue resolution, improving KPI tracking and data-driven decision-

making for software quality metrics. Documented processes and project outcomes in Confluence and created a User Guide to enhance user

adoption and simplify the onboarding process.

Software Engineer Mercedes-Benz Research and Development, Bengaluru, India Jan 2020 – June 2020

• Designed and developed a team-building platform using React, Node.js, and PostgreSQL, analyzing employee participation data pre- and post-

implementation, leading to a 20% increase in engagement.

• Conducted data analysis on user behavior, tracked key metrics, and created visual reports in Power BI to assess the app’s impact on collaboration

and identify areas for improvement.

• Engaged with leadership to ensure system scalability and efficiency, applying Agile methodologies for continuous platform improvements.

ACADEMIC PROJECTS

Employee Attrition Analysis and Retention Strategy (Python, Excel, Logistic Regression)

• Performed exploratory data analysis (EDA) using Python and Excel, applying hypothesis testing (t-tests, chi-square) and correlation analysis to

uncover key factors driving attrition, such as salary gaps, job satisfaction, and department trends.

• Developed a logistic regression model with feature selection and cross-validation, accurately predicting high-risk employee segments.

• Recommended data-driven retention strategies, including personalized career development plans, salary adjustments, and work-life balance initiatives,

leading significant reduction in turnover risk and 10% improvements in HR decision-making efficiency.

Walmart Sales Forecasting (Python, XGBoost, Tableau)

• Developed a predictive model to forecast weekly sales for Walmart stores, achieving 95% accuracy and reducing inventory costs by 20%.

• Preprocessed data, including handling missing values, transforming features, and incorporating seasonal and holiday adjustments to improve model

accuracy.

• Visualized forecasting results and actionable insights in Tableau to drive data-informed decisions.

Spotify Data Analysis (PostgreSQL)

• Normalized Spotify dataset in PostgreSQL, optimizing data integrity and query performance.

• Analyzed track performance, artist popularity, and album trends using SQL queries, uncovering key insights into music patterns and streaming

trends.

Eligible to work in the U.S. under F1 OPT (Optional Practical Training).

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