Machine Learning Business Analyst

CHAITANYA SURABATTUNI

+1-945-***-**** ******************@*****.*** linkedin.com/in/chaitanyasurabattuni EDUCATION

University of North Texas, TX

Master's, Artificial Intelligence (Machine Learning specialization) 3.75 GPA Aug 2023 - May 2025 Visvesvaraya Technological University, Bangalore

Bachelor's, Electronics and Communications 3.7 GPA Oct 2018 - May 2025 PROFESSIONAL EXPERIENCE

Graduate Assistant - Data Analytics, University of North Texas (UNT)May 2024 - Dec 2024

-Developed interactive dashboards in Tableau to analyze enrollment trends and student retention rates, enabling data-driven strategies to improve academic performance and engagement.

-Built predictive models using machine learning algorithms (e.g., Random Forest, Logistic Regression) to forecast enrollment patterns, aiding in resource allocation and policy planning.

Business Analyst, CapGemini Bangalore Apr 2021 - June 2023 Advanced Data Analysis and Reporting

-Conducted market research and trend analysis, leveraging Power BI and Tableau to deliver actionable insights, enabling data-driven strategic planning for clients.

-Designed predictive models using machine learning techniques (e.g., Random Forest, XGBoost) to forecast customer behavior, improving decision-making accuracy by 30%.

-Built real-time KPI dashboards for monitoring performance metrics across departments, reducing reporting time by 40% and enhancing operational efficiency.

Process Optimization and Automation

-Implemented Robotic Process Automation (RPA) to streamline repetitive tasks, achieving a 40% reduction in manual errors and saving 15 hours per week.

-Built and maintained data pipelines using Python and ETL tools, ensuring seamless data flow between multiple sources

-Conducted gap analysis of existing workflows and proposed process reengineering solutions, reducing operational costs by 25%.

-Led Lean Six Sigma projects to optimize supply chain processes, reducing lead times by 20% while maintaining quality standards. Solution Implementation and Testing

-Coordinated User Acceptance Testing (UAT) sessions with end-users, ensuring solutions met functional and non-functional requirements while documenting feedback for iterative improvements.

-Collaborated with IT teams to execute system integration testing, ensuring seamless data flow between legacy systems and new platforms.

-Provided post-implementation support by conducting training sessions and developing user manuals, ensuring smooth adoption of new systems among stakeholders.

ACADEMIC EXPERIENCE

Predicting Credit Card Approvals

-Developed a logistic regression model to predict credit card approvals, achieving 85% accuracy by preprocessing data (imputation, normalization, and SMOTE) and optimizing hyperparameters with GridSearchCV.

-Evaluated model performance using precision, recall, and F1-score, and presented insights through an interactive Tableau dashboard. Reducing Traffic Mortality in the USA.

-Analyzed traffic fatality data using multivariate regression and K-Means clustering to identify high-risk factors like weather and road types.

-Visualized findings with Python (Matplotlib, Seaborn) to propose actionable strategies for reducing traffic-related deaths. KNOWLEDGE STACK

-Programming & Data Analysis: Python, R, SQL, PySpark, Hadoop, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn.

-Data Visualization & Machine Learning: Tableau, Power BI, Logistic Regression, Random Forest, XGBoost, K-Means Clustering.

-Database & Automation Tools: MySQL, AWS Athena, Data Warehousing, Robotic Process Automation (RPA), Apache Airflow. Certifications: Python, PyTorch, NLP, CNN, AWS Solutions Architect Associate, SQL, TensorFlow

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