Machine Learning Power Bi

ROHAN REDDYMALA

+1-940-***-**** ***************@*****.*** www.linkedin.com/in/rohan-reddymala-0b0b7a28b

SUMMARY

Ambitious and detail-oriented Business Analytics professional with a Master's degree and a passion for using data to drive strategic business decisions. Experienced in advanced analytics, machine learning, data visualization, and database management. Demonstrated capability to collaborate with cross-functional teams to discover insights, streamline processes, and solve complex business issues. Strong communication skills combined with a technical skill set that includes SQL, Python, R, Power BI, and Tableau. Committed to delivering measurable value through fact-based solutions.

EDUCATION

University of North Texas, Denton, Texas Aug 2023 – May 2025

Master’s in Business Analytics

Bachelor of Commerce in Computers June 2017 – June 2020

Indian Institute of Management and Commerce, Osmania University, Hyderabad

TECHNICAL SKILLS

• Programming Languages: Python (NumPy, pandas, Matplotlib, scikit-Learn, SciPy), MySQL, SAS, NoSQL, R, VBA

• Tools: Microsoft Fabric, Tableau, Power BI, Alteryx, SAS Miner, MS Excel

• Certifications: Microsoft Certified: Fabric Analytics Engineer Associate, Power BI Essential Training – NASBA, SQL by data camp, R-language by data camp

EXPERIENCE

Carelon Global Solutions – Hyderabad, India Dec 2020 – Aug 2023

Business Analyst – Healthcare Domain

• Analyzed healthcare claims data using SQL and Excel to identify processing inefficiencies and reduce claim denials.

• Built interactive Tableau dashboards to track key performance metrics and provide issue trends.

• Partnered with cross-functional teams to resolve provider escalations and streamline operational workflows.

• Generated actionable insights through root cause analysis and presented findings to leadership for data-driven decisions.

• Developed automated reports to support strategic planning and improve claims turnaround time.

PROJECTS

• Water Pump Functionality Prediction: Predicted water pump functionality using decision trees, logistic regression, neural networks, and random forest. Achieved 88.18% accuracy with Decision Tree 2 after extensive data cleaning and feature selection in SAS Enterprise Miner.

• Exploring Global Data Companies Salary Trends: Explored global salary trends in data science roles using Tableau, analyzing how job title, experience, company size, and location impact pay. Built interactive dashboards and visualizations to uncover compensation disparities and support data-driven hiring strategies.

• Multimodal Gaze Analytics for Emotion Recognition: Developed machine learning models using eye-tracking data to predict emotion recognition accuracy, achieving 91.25% with Random Forest. Analyzed gaze patterns, pupil size, and demographics to support personalized emotion-aware systems in healthcare and e-learning.

• Loan Approval Analysis Using Machine Learning: (python) Built predictive models using Random Forest and Logistic Regression to classify loan approvals, achieving 93% accuracy and identifying key features like previous defaults and income ratio to improve fair lending decisions.

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