Systems Engineer Data

SAI RUCHITHA BABU CHIRUVANUR RAMESH BABU

+1-774-***-**** • ********************@******.*** • LinkedIn

Dartmouth, Massachusetts, USA

PROFESSIONAL SUMMARY

Accomplished Data Engineer and Systems Engineer with a proven track record of optimizing complex data systems and software development practices. Expert in the agile development process, software builds, and ongoing application support. Demonstrates a strong willingness to learn new technologies and leverage them effectively in an agile team setting. Highly motivated with a demonstrated ability to quickly adapt to new environments and technology stacks, contributing effectively to team goals and software delivery. EDUCATION

University of Massachusetts Dartmouth, Summer 2024 Masters in Data Science 3.9 GPA

• Relevant coursework - Database Design, Advance Machine Learning, Big Data Analysis, Advance Data Mining, Cyber-Physical Systems, Business Analytics and Data Mining.

• Secretary of Cyber Secure Computing Club, UMassD WORK EXPERIENCE

INFOSYS Bengaluru, India

Systems Engineer Apr 2021 - Dec 2022

• Worked in the SAP domain at Infosys and engaged in the Migration of data from ECC to HANA System activities using SLT, IDOC, and MFT.

• Worked on the Master Data migration and ongoing data replication related activities for S4 HANA boxes from ECC Systems using the SLT.

• All the configurations of SLT such as creating MTID and configuring RFC for sender/receiver side, and enabling 95% of replications were performed in P&G project.

• Also worked on IDOC which helped in setting up the tables, for moving the content of the tables that have delta changes from one system to another in MDS4 migration activity. COVANCE Bengaluru, India

Intern Jan 2020 - Jul 2020

• Worked on Power BI tool and implemented Quality Analysis Dashboards for 7 teams within the company.

• Designed dashboards to track employee performance on a daily, monthly, and yearly basis.

• Provided comprehensive data visualization for team performance evaluation which increased employee performance by 57%.

• Streamlined quality analysis processes for each team. PROJECTS & RESEARCH

Insurance Database - AWS DynamoDB, Mango DB Apr 2023

• Designed and implemented a robust NoSQL database model using AWS DynamoDB and MongoDB, managing complex relationships for efficient policy categorization.

• Utilized PartiQL for streamlined data extraction and enhanced filtering, showcasing strong database querying skills.

Handwritten Digit Recognition - Python, scikit-learn, and ML algorithms. July 2023

• Implemented KNN, SVM, RFC algorithms using Python for MNIST dataset digit recognition.

• Led preprocessing, including scaling, flattening, and optional dimensionality reduction and applied ensemble learning principles in Random Forest Classifier, enhancing model robustness, and achieving accurate predictions for handwritten digit recognition.

• Cross-validated and optimized models, emphasizing proficiency in Python, scikit-learn, and ML evaluation metrics.

Income Prediction Project - Python, Machine Learning, Data Visualization Aug 2023

• Developed a multi-model strategy incorporating Gradient Boosting, SVM, Random Forest, and Decision Trees.

• Conducted comprehensive correlation analysis, strategically streamlining features for model efficiency.

• Designed a user-friendly GUI using Tkinter, facilitating real-time predictions and contributing to policy insights.

Exploration of Fatal Police Shootings in the U.S – Python, Decision Tree Analysis, matplotlib, seaborn Nov 2023

• Analyzed a dataset from the Washington Post on fatal police shootings, employing KNN imputation for data completeness and using ANOVA and Chi-square tests

• Created decision tree models that predicted the likelihood of fatal outcomes in police encounters with an accuracy of 94%, focusing on the impacts of body cameras and racial disparities.

• Produced data visualizations, including bar graphs and decision trees, to delineate trends in police shootings over a seven-year period, aiding in the identification and understanding of key predictive factors.

Healthcare Data Analysis - Azure Databricks, Power BI Nov 2023

• Worked on patient and hospital data, analyzed using Azure Databricks for processing and Power BI for visualization and explored seasonal trends in medical conditions and admissions to enhance healthcare planning.

• Collected diverse patient data, securely stored in Azure Blob Storage for accessibility and scalability.

• Utilized analytical models for robust data processing, resulting in valuable insights for improved patient care.

TECHNICAL SKILLS

• Programming languages known: C, Java, Python, R.

• Database: SQL Server, MySQL, MongoDB, DynamoDB.

• Visualization Tools: Matplotlib, Seaborn, Power BI, Google BI, Tableau.

• ERP Tool: SAP ABAP

• Frameworks/Libraries: Keras, NumPy, Git, Pandas, HTML, CSS.

• Cloud Technologies: AWS (Sage maker, S3, Redshift, Athena), Azure Databricks

• Data Transformation Tools: OpenRefine.

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