Hey, I'm Rohith Reddy Kolanu
I'm a
"Results-driven Data Science, Artificial Intelligence, Machine Learning and Analytics professional transforming complex data into scalable AI insights that drive decisions and business growth."
About
I’m Rohith Reddy Kolanu, a Data Science, Artificial Intelligence, Machine Learning, and Analytics professional currently pursuing a Post Graduate Program in Artificial Intelligence & Machine Learning: Business Applications at The University of Texas at Austin. My academic foundation is rooted in advanced machine learning techniques, statistical reasoning, Python-driven analytics, data visualization, and modern business intelligence frameworks.
I enjoy working at the intersection of AI, data, and business, uncovering patterns in complex datasets, building predictive models, and translating analytical outcomes into actionable insights that support strategic decision-making. My technical skill set includes Python, SQL, Power BI, machine learning, NLP with Generative AI, computer vision, and statistical analysis, enabling me to solve real-world business problems with clarity and impact.
Education
Post Graduate Program in Artificial Intelligence and Machine Learning: Business Applications
Relevant Coursework:
Python Foundations, Machine Learning, Advanced Machine Learning, Introduction to Neural Networks, Natural Language Processing with Generative AI, Introduction to Computer Vision, Model Deployment
Visit WebsiteMaster of Science in Business Analytics, Data Analytics
Relevant Coursework:
Data Management, Business Intelligence, Business Applications with Python, Machine Learning, Project Management, Financial Technology, Data Science, Data Visualization, Artificial Intelligence
Visit WebsiteBachelor of Business Administration, Finance
Relevant Coursework:
Economics, Organization Behavior, Statistics, Accounting, Marketing Research, Risk Analysis, Insurance Services, Business Law & Ethics, Management Science, Banking, Investment Analysis
Visit WebsiteExperience
Process Analyst
- Designed and automated an Excel-based utilization tracking system, reducing manual effort by 90%, standardizing calculations, and enabling accurate workforce analytics leveraged through monthly Power BI and PowerPoint reports.
- Built and delivered monthly performance dashboards using Power BI and Excel, improving reporting accuracy and visibility of key utilization metrics, trends, and KPIs to support data-driven operational decisions.
- Analyzed and processed over 2,000 client documents, websites, and HTML emails with 99% accuracy, ensuring SLA compliance while maintaining high data quality, validation standards, and process consistency.
- Handled 300+ operational requests during peak cycles with 99% accuracy, reducing turnaround time by 20% through workflow optimization, prioritization logic, and continuous process improvement initiatives.
- Collaborated cross-functionally with Desktop Publishing and Client-Facing teams to validate data outputs, improve reporting reliability, and translate operational data into actionable business insights.
Projects
Insights into Customer Shopping Behavior
- Project analyzes 3,900 retail transactions across 18 attributes including age, gender, product, price, payment, and frequency, enabling structured exploration of customer purchasing behavior using a clean, tabular dataset.
- Data pipeline integrates CSV ingestion, SQL querying, Python EDA, and Power BI visualization, transforming raw transaction-level data into aggregated KPIs such as average spend, purchase frequency, and category-level revenue.
- Quantitative analysis highlights purchase amounts, review ratings, prior purchase counts, and discount usage, allowing comparison across demographics, seasons, locations, and subscription versus non-subscription customers.
- Interactive Power BI dashboard presents trends by category, gender, and season, supporting business decisions through measurable outputs like transaction counts, average order value, and percentage use of promos or discounts.
- Overall, it demonstrates an end-to-end analytics workflow, combining multiple tools and KPIs to convert customer-level data into actionable retail insights for data-driven decision making and strategic business performance optimization.
Loan Default Risk Assessment Using Machine Learning
- Developed a machine learning-based loan default prediction solution using demographic, financial, and credit history features, focusing on minimizing false negatives and improving credit risk assessment through recall-driven model optimization.
- Conducted comprehensive exploratory data analysis including univariate, bivariate, correlation, and class imbalance analysis, identifying key relationships and outliers influencing loan default behavior and overall model performance.
- Built a robust preprocessing pipeline incorporating outlier treatment, feature scaling, categorical encoding, SMOTE-based class imbalance handling, and stratified train–test splitting to ensure reliable and unbiased model training.
- Trained and evaluated seven supervised classification models, with Decision Tree achieving the best performance at 89.21% accuracy and 0.895 F1-score, while SVM delivered strong results with 87.99% accuracy and 0.886 F1-score.
- Compared models using accuracy, precision, recall, F1-score, and ROC-AUC, demonstrating that tree-based and ensemble methods outperform linear models, enabling data-driven, risk-based lending and portfolio loss reduction strategies.
Predicting Used Car Prices Through a Machine Learning-Based Regression Model
- Developed a machine learning–based regression framework to predict used car prices, benchmarking multiple models and identifying XGBoost as the top performer with lowest Test RMSE of 0.162 and Test MAE of 0.128, demonstrating strong generalization capability.
- Conducted end-to-end exploratory data analysis and feature engineering on vehicle attributes such as age, mileage, engine capacity, fuel type, and ownership, uncovering key price drivers and reducing noise impacting regression model accuracy.
- Built and evaluated regression models including OLS Regression, Random Forest, and XGBoost, comparing performance using RMSE, MAE, and MAPE, and ranking models based on test metrics to ensure objective, data-driven selection.
- Achieved superior predictive accuracy with XGBoost, outperforming Random Forest (Test RMSE = 0.203) and OLS Regression (Test RMSE = 0.239), and ranking 1st across RMSE, MAE, and MAPE in overall model performance.
- Translated model outputs into actionable pricing insights, enabling data-driven valuation strategies, improved inventory pricing accuracy, and reduced estimation error through advanced ensemble methods and rigorous evaluation.
The Optimal Places to Work & Live in USA
- Designed and developed an interactive Excel dashboard analyzing socio-economic indicators across 15 U.S. states, consolidating multi-source datasets to provide insights on GDP, population, income, job growth, migration, and cost of living.
- Automated ETL workflows using Excel VBA macros to process, clean, and consolidate multiple raw datasets, reducing manual data preparation time and enabling real-time updates for KPI tracking and decision support.
- Built dynamic visualizations including KPI cards, heat-formatted tables, trend charts, and geographic mapping to compare metrics such as GDP ($6.2T total), average income ($44.5K), job growth (2.33%), and migration rate (0.45%).
- Implemented advanced filtering, sorting, and slicer controls to enable state-level drill-downs across economic, demographic, health, infrastructure, and crime metrics, improving analytical flexibility and stakeholder usability.
- Delivered actionable insights by identifying optimal states to work and live based on multi-factor analysis of income, job growth, graduation rates, poverty, crime, internet speed, and cost of living, supporting data-driven planning and policy decisions.
Factors Influencing Cryptocurrency Investment Decisions in India
- Conducted an academic research study analyzing factors influencing cryptocurrency investment decisions in India, focusing on Bitcoin and Ethereum adoption through behavioral finance, market trends, risk perception, and regulatory impact analysis.
- Designed and executed primary research using survey questionnaires collected from 50 respondents, supplemented with secondary data from journals, market reports, and online resources to assess investor awareness, risk tolerance, and willingness to invest.
- Performed statistical analysis using Microsoft Excel to evaluate key decision drivers including financial literacy, market volatility, regulatory uncertainty, and technological awareness affecting crypto investment behavior in emerging markets.
- Compared Bitcoin and Ethereum across various metrics like Future growth prospects, Use of crypto currencies for illegal purposes, Historical performance, Cryptocurrencies as store of value, and Willingness to buy among Indian retail investors.
- Delivered actionable insights highlighting key drivers such as market sentiment and innovation, challenges including lack of regulation and security risks, and future prospects for mainstream adoption with improved policy frameworks and financial literacy.
Skills
Programming Languages, Databases & Version Control
Data Analysis, Visualization & Business Intelligence
Machine Learning & Artificial Intelligence
Deep Learning, Generative AI & Advanced AI Frameworks
Big Data, Cloud Platforms & Data Engineering
Model Deployment, MLOps & Development Tools
Web Development
Collaboration & Reporting Tools
Data & Research Skills
Finance & Investment
Project & Process Management
Soft Skills
Certifications
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Learning Excel Desktop (Microsoft 365)
Offered by LinkedIn Learning — Verify Certificate
Investment Banking: Financial Analysis and Valuation
Offered by University of Illinois Urbana-Champaign through Coursera — Verify Certificate
Testimonials
What my coworkers and managers say about me.
Rohith is an outstanding coworker whose presence significantly enhances the work environment. His exceptional ability to create a comfortable and open space for communication sets him apart...
Rohith is an outstanding coworker whose presence significantly enhances the work environment. His exceptional ability to create a comfortable and open space for communication sets him apart. This quality makes interactions with him easy and effective, fostering a positive atmosphere where ideas and concerns can be shared freely. This openness is crucial for team cohesion and productivity, as it encourages collaboration and mutual respect.
He has the traits which I like the most: problem-solving and the ability to learn new things through research.
One of Rohith’s most notable attributes is his problem-solving skills. He approaches challenges with a keen analytical mind, breaking down complex issues into manageable components. This methodical approach allows him to develop effective solutions that address the root causes of problems rather than just their symptoms. His problem-solving abilities are particularly valuable in today’s fast-paced and ever-changing work environment, where quick and effective responses to issues are often required. Rohith’s skill in this area not only resolves immediate problems but also contributes to long-term improvements and innovations within the team.
In addition to his problem-solving prowess, Rohith excels in research. In an era where accurate and reliable information is essential, his ability to conduct thorough research is a significant asset. He is adept at gathering relevant data, analyzing it critically, and presenting findings in a clear and actionable manner. This proficiency ensures that decisions are based on solid evidence and up-to-date knowledge, which is crucial for making informed choices and staying ahead in a competitive landscape. Rohith’s research skills support the team in various ways, from strategic planning to staying informed about industry trends and best practices.
Beyond these core traits, Rohith’s enthusiasm for learning new tasks is noteworthy. His eagerness to expand his skills and knowledge keeps him engaged and adaptable. This continual learning not only benefits him personally but also contributes to the team’s overall growth and adaptability. Rohith’s curiosity drives him to explore new areas and embrace emerging trends, which can lead to innovative solutions and fresh perspectives.
I am writing to highly recommend Rohith, who has been an invaluable member of our team for the past two years. Since joining us as a fresher, Rohith has demonstrated remarkable growth and has consistently proven to be an exceptional team player...
I am writing to highly recommend Rohith, who has been an invaluable member of our team for the past two years. Since joining us as a fresher, Rohith has demonstrated remarkable growth and has consistently proven to be an exceptional team player. His contributions to our team’s success and efficiency have been significant, and his dedication to continuous learning and improvement is truly commendable.
From the moment Rohith joined our team, it was evident that he possessed a keen desire to learn and grow. He quickly acclimated to our work environment and took every opportunity to expand his knowledge and skills. His enthusiasm for learning new things is infectious, and he has a natural talent for translating his newfound knowledge into practical applications that benefit the entire team.
One of Rohith’s most admirable qualities is his proactive approach to team building and efficiency. He has consistently taken the initiative to identify areas where improvements can be made and has proposed and implemented effective solutions. His efforts have not only streamlined our processes but also enhanced our overall productivity. Rohith’s ability to think critically and act decisively has made a significant impact on our team’s success.
In addition to his personal growth, Rohith has shown a genuine interest in helping his colleagues develop their skills. He regularly takes the initiative to organize training sessions and workshops, sharing his knowledge and expertise with the team. His willingness to invest time in the growth of his peers has fostered a collaborative and supportive team culture, which has been instrumental in our collective achievements.
Rohith’s dedication to continuous improvement and his commitment to helping others are qualities that set him apart. He has not only been an asset to our team but also an exemplary role model for his peers. I have no doubt that he will continue to excel and make meaningful contributions wherever he goes.
His drive, initiative, and collaborative spirit make him a valuable addition to any team. I wholeheartedly recommend Rohith for any opportunity he pursues.
Contact
Ready to collaborate on exciting projects or discuss opportunities? I'd love to hear from you.
Get in Touch
I'm always open to discussing new opportunities, collaborations, or just having a conversation. Feel free to reach out through any of the channels below.
rohithreddy.kolanu25@gmail.com
Phone
+1 (413) 315-7384
Location
Amherst, MA, USA