Hi, my name is Abhishek Gowda T
I'm a Software Developer / Data Science Student.

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About me

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Motivated and dedicated software developer with a strong commitment to continuous learning and professional growth. Passionate about working with cutting-edge technologies and delivering high-quality solutions. Seeking to contribute effectively to organizational success through a positive attitude, strong work ethic, and a focus on innovation and collaboration.

Location: Berlin, Germany | Phone: (+49) 15510733747 | Email: abhishekgowdat05@gmail.com | LinkedIn: LinkedIn Profile

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Work Experience

Software Developer | ERUNA TECHNOLOGIES INDIA PRIVATE LIMITED (Bengaluru, India)

20/03/2025 - 28/09/2025

  • Used .NET Core (8.0) to design and develop RESTful APIs for mobile and web apps (HRMS, Payroll, Attendance).
  • Implemented CQRS pattern to separate concerns, enhancing scalability.
  • Used Entity Framework Core (Code-first migrations, LINQ) and Dependency Injection.
  • Combined Role-based authorization with JWT authentication for security.
  • Documented APIs using Swagger for frontend integration.
  • Used Jira for task management and Git for version control.
  • Tech Stack: C#, .NET Core, Amazon S3, MongoDB, PostgreSQL, Postman, Visual Studio.

Software Developer | EMPLOYEE BASED SYSTEMS LLC. (Bengaluru, India)

01/01/2023 - 31/01/2025

  • Payroll Management System: Developed RESTful Web APIs, dynamic ASP.NET UIs, and RDLC reports. Used Database First Approach.
  • HR Management System (HRMS): Maintained Web APIs, optimized SQL queries, and authored technical documentation.
  • Time and Attendance System: Implemented timesheet features and responsive ASP.NET UIs.
  • Punching Clocks Integration: Developed Windows Applications (WebForms) for data synchronization.
  • Punch Clock Windows Service: Built background services for data processing.
  • Mobile App: Designed a Xamarin-based Android app for employee self-service.
  • Tech Stack: C#, .NET Core/Framework, MS SQL, Xamarin, HTML, CSS, JavaScript, jQuery, Bootstrap 5.

Education

Master's in Data Science | University of Europe for Applied Sciences (Berlin, Germany)

29/09/2025 - Current | EQF Level 7

Bachelor of Engineering (Computer Science) | Rajarajeswari College of Engineering (Bengaluru, India)

2018 - 2022 | Final Grade: 7.27 CGPA

Pre-University | Sri Vani Vidhya Kendra PU College (Bengaluru, India)

2016 - 2018 | Final Grade: 58%

SSLC | The New Cambridge High School (Bengaluru, India)

2016 | Final Grade: 74%

Skills

Programming

C#, Python, Core Java

Databases

PostgreSQL, MongoDB, MS SQL, MySQL

Web

HTML, CSS, React.js, JavaScript, Bootstrap

ASP.NET

Web API, .NET Core, CQRS, Entity Framework, ADO.NET

Tools

Windows Services, RDLC Reports, Xamarin, TFS, Git

Publications

"Multiclass Pathology Classification in a Voice Signal using Deep Learning Technique"

Published in International Journal of Research and Analytical Reviews (IJRAR), Vol 5, Issue 3, 2022.

Projects

Employee Self-Service Chatbot

Created an AI chatbot using Llama3 (Ollama) to answer HR queries (leave balance, etc.). Implemented session-based memory and natural language processing. Tech: FastAPI, Python, PostgreSQL, REST API, Swagger UI.

Source Code
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Customer Churn Prediction

Built a churn prediction system (Random Forest, 80% accuracy) with a Streamlit web app. Tech: Python, Pandas, Scikit-Learn, Plotly, Streamlit.

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Respiratory Diagnosis Expert System

Developed a rule-based system for symptom interpretation using explicit IF-THEN logic.

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Supply Chain Analytics – Just-In-Time Company

A data analytics project focused on evaluating sales performance, inventory efficiency, and shipment reliability in a JIT supply chain environment. Uses Python with Pandas and NumPy for data cleaning, preprocessing, feature engineering, and exploratory data analysis. Applied ABC–XYZ inventory segmentation to prioritize products based on revenue contribution and demand variability. Visualized using Power BI with interactive dashboards for key performance indicators, inventory risks, and shipping performance. Demonstrates descriptive and diagnostic analytics for data-driven decision-making in supply chain management.

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Contact

Let's connect! Feel free to reach out for opportunities or collaborations.

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