Data Analyst Machine Learning

MALLIKARJUNA KAMMARI

Cincinnati, Ohio ********@****.**.*** https://www.linkedin.com/in/mallikarjuna-k-a2b192182 +1-513-***-****

PROFESSIONAL SUMMARY : -

Detail-oriented and analytical professional with 2 years of experience as an analyst, Engineer role. Exceptional customer service and problem-solving skills with the ability to multitask effectively. Highly adaptable and committed to continuous learning, I am excited to contribute to innovative projects and rapidly integrate into new and challenging environments. Strong knowledge of software development best practices and experience handling technical issues efficiently.

PROFESSIONAL EXPERIENCE : -

DBS-Tech - Data Analyst Aug 2022-Aug 2024

Responsibility:

●Led migration of complex data mart from SAS to PySpark, improving processing speed by 40% and data accuracy, while completing the project ahead of schedule.

●Optimized data workflows and converted SAS scripts to PySpark, reducing report generation time by 30% and enhancing system performance.

●Collaborated with architects and business users to design and implement PySpark models, meeting client requirements and generating new reports.

●Managed a team of 5 analysts to ensure timely, accurate financial reporting and improved KPI visibility through dashboard development.

●Achieved 100% data accuracy through unit testing of migrated scripts, ensuring flawless data match and performance.

●Improved query performance by analyzing and optimizing execution plans for slow-running queries, boosting overall system efficiency.

●Utilized Bitbucket for version control and participated in agile workflows, ensuring smooth collaboration and on-time project delivery.

EDUCATION : -

Master’s Degree - University of Cincinnati (3.6/4)

●Cincinnati, Ohio Aug 2024-April 2026

●Master’s Science (Computer Science).

Bachelor’s Degree - Jawaharlal Nehru Technological University (7.5/10)

●Hyderabad, Telangana Aug 2018-Jul 2022

●Bachelor of Technology (Information Technology).

TECHNICAL SKILLS :-

●Programming Languages & Frameworks: PYTHON, JAVA, PYSPARK, SAS(Statistical Analysis System), HTML, CSS, JavaScript, React, Web API

●Data Management: Data extraction, cleaning, transformation, and visualization.

●Big Data Technologies: PySpark, Hadoop, Databricks

●Databases: Microsoft SQL Server (MSSQL), MYSQL

●Data Visualization: Power BI, Tableau, Matplotlib, PANDAS

●Version Control: Git, Bitbucket.

●Business Tools: Google Workspace (Docs, Sheets, Slides), Jira, Confluence, Microsoft Office (Word, Excel, PowerPoint)

Personal Projects: -

Retail Data Analytics & Machine Learning on Azure Cloud (10/2024 - 12/2024)

●Designed and implemented an end-to-end solution for analyzing retail data using Azure Cloud services.

●Focused on data ingestion, transformation, analysis, and machine learning to generate actionable insights.

●Developed an interactive web application to visualize customer engagement and spending behaviors.

●Analyzed anonymized retail data from 84.51 /Kroger to improve customer experience and engagement.

●Addressed key business questions including customer segmentation, loyalty program impact, basket analysis, and demand forecasting.

●Applied machine learning models for churn prediction, customer lifetime value estimation, and socio-economic influence analysis.

●Ensured data quality and consistency through validation techniques and visualized findings using Power BI and Python libraries.

Life Expectancy Prediction Using Machine Learning (10/2024 - 12/2024)

oDeveloped a regression model to predict life expectancy for 193 countries using data from 2000–2015.

oAnalyzed the impact of immunization (Hepatitis B, Polio, Diphtheria), mortality rates, economic, and social factors.

oPreprocessed and cleaned datasets using statistical analysis to handle missing data effectively.

oDerived insights to identify key factors contributing to low life expectancy, aiding targeted improvement strategies.

oTools/Technologies: Python, PySpark, MYSQL, Spark, ML, Pandas, Scikit-learn, Matplotlib, WHO/UN data.

QR based Inventory management mobile application using android and firebase (10/2021 - 12/2021)

●Developed an Android-based mobile application for inventory management using QR code scanning technology.

●Integrated Firebase for real-time data synchronization and cloud storage, allowing inventory updates from multiple devices.

●Designed an intuitive user interface for easy scanning and updating of inventory items, reducing manual effort.

●Implemented functionalities for tracking stock levels, item history, and generating real-time reports.

Certifications :-

●Programming in C

●Programming in Java

Introduction to Machine Learning

●Social Networks

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