Workday integrations, Machine learning

SREEJA BODANAPU

Cincinnati, OH +1-513-***-**** ****************@*****.*** LinkedIn: Sreeja Bodanapu EDUCATION

University of Cincinnati Cincinnati, Ohio, USA

Master of Science, Information Technology; GPA 4.0/4.0 August 2023 – December 2024 Courses: Web Application Programming and Hacking (WAPH), Machine Learning and Data Mining, Principles of Cyber Security G. Narayanamma Institute of Technology & Science (Affiliated to JNTUH) Hyderabad, India Bachelor of Technology, Electronics and Communication Engineering; GPA 8.55/10 August 2017 - June 2021 Courses: Java Programming, Database Management Systems, Computer Networks, Microprocessors and Microcontrollers SKILLS AND CERTIFICATIONS

Programming Languages: C, Java, Python, JavaScript, HTML, PHP, CSS, MySQL, XML, XSLT Development Tools: Workday Integrations, Visual Studio, Visual studio code Technologies: SOAP Rest APIs, Git, Postman, MATLAB, Multisim WORK EXPERIENCE

Analyst, Deloitte USI September 2021 – July 2023

● Involved in full cycle including requirement gathering and analysis, design, development, testing and implementation of Workday integrations.

● Collaborated with clients and external vendors to integrate 26 systems with Workday, optimizing data transfer efficiency. Developed integration systems across various modules including Workday HCM, Time Tracking, Benefits, and Payroll.

● Worked on designing and developing custom integrations using Workday tools like EIBs, Connectors, Studio and APIs.

● Configured Workday's business processes to automate HR functions like employee lifecycle management and payroll processing, while also implementing security protocols such as role-based access control and data encryption during file transfers.

● Configured Workday job functionalities with appropriate security measures for posting jobs and receiving applications on external sites such as LinkedIn, indeed, and Handshake.

● Hands-on experience with Agile Methodology and entire Defect Life cycle from opening to closing a defect. ACADEMIC PROJECTS

Fake News Detection - A comparative study: Built a machine learning model to detect fake news within a given text. Feature extraction was performed on the data using the TF-IDF vectorization technique. The extracted features were then utilized with algorithms including Decision Tree, Naive Bayes, Random Forest, Gradient Boosting, and Support Vector Machine to identify the most suitable model for fake news detection.

Mini-Facebook web application: Created a dynamic web application for the WAPH course integrates PHP, HTML, MySQL. Features of this application include user registration, post creation, commenting, and chat functionality. Admin users oversee user access rights, ensuring seamless interaction for all users.

Automatic Announcement System: Developed an announcement system that sends recorded announcements at specified times. This system was built using Raspberry Pi, PHP, HTML, and MySQL. CERTIFICATIONS

Workday Integrations October 2021

Workday Custom Integrations October 2021

Workday HCM Consulting core October 2021

COURSES

Python Essential Training - LinkedIn

Data Science Foundations: Python Scientific Stack - LinkedIn Applied Machine Learning: Feature Engineering - LinkedIn AI for Everyone - Coursera

HONORS AND ACHIEVEMENTS

● Received Project Performance Recognition Award in Deloitte during first Workday Project for demonstrating exceptional performance by efficiently developing integrations ahead of project timelines, enabling seamless data synchronization.

● Awarded 1st Prize for presenting a paper on 'Eye Gaze Controlled Robot' at Aakruthi2020, held at Osmania University

● Received Academic Excellence Award at GNITS for consistently achieving top grades in coursework within the class.

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