Nikhil Matcha
Development
Colorado, United States
Skills
Machine Learning (ML)
About
Nikhil Matcha's skills align with IT R&D Professionals (Information and Communication Technology). Nikhil also has skills associated with Programmers (Information and Communication Technology). Nikhil Matcha has 5 years of work experience.
View more
Work Experience
Member of Technical Staff (Java Developer)
Techmojo Solutions
July 2022 - July 2023
- Responsibilities: End-to-end development for online casino providers, adept at employing microservices architecture to address specific feature requirements. Key responsibilities include vendor integration, user registration, cashier transaction management, and regulatory compliance services. Successfully integrated new vendors, games, and payment providers to facilitate seamless cash transactions and enhance platform functionality. Developed user registration service with robust regulatory compliance measures, ensuring adherence to country-specific regulations for end users. Designed and implemented a frontend website for vendors to conduct online casino operations to deliver an intuitive user experience. Diligently adhered to Agile methodologies and utilised the Scrum framework on a daily basis to effectively manage and deliver projects within designated timelines. Proactively engaged in learning various software development methodologies to enhance project execution and team collaboration. Demonstrated leadership and initiative by assuming responsibilities as needed, fostering a collaborative and efficient work environment. Technologies used: Java, Spring Boot, Microservices, MySQL, JavaScript, HTML, CSS, React.js, Agile, MongoDB, Kubernetes
Co-op intern
Multiverz
May 2021 - July 2021
- Responsibilities: Led the development of a Natural Language Processing (NLP) model aimed at extracting key skills from diverse job postings. This model laid the foundation to the creation of an innovative application, empowering students and government entities to pinpoint crucial industry skills for tailored training strategies. Significantly boosted accuracy to an impressive 90% by integrating a Named Entity Recognition (NER) model, demonstrating a commitment to precision and excellence in skill identification. Technologies used: Python, NLP, Named Entity Recognition (NER)
Data analytics Intern
Tikaj Technologies, Gurgaon
October 2019 - December 2019
- Responsibilities: Initiated and executed a project focused on data acquisition from diverse local businesses across tier-2 and tier-3 cities as well as small towns, utilising multiple websites as data sources. Spearheaded the development of a comprehensive application offering centralised access to business information across various locales. Implemented a Python-based web crawler tool to automate data retrieval processes, significantly enhancing efficiency and reducing scraping time for diverse website formats. Technologies used: Python, beautifulsoup, scrappy, selenium, MongoDB.
Graduate Research Assistant
ColoradoStateUniversity, Fort Collins
August 2023 - Present
- Responsibilities: Collaborated with Dr. Yiwen Gao on cyber security research, contributing to data collection and analysis efforts. Utilised advanced web scraping techniques to gather data from diverse sources and used the fuzzywuzzy library to identify and analyse similarities within datasets. Automated the data scraping process to enhance efficiency and accuracy, demonstrating strong problem-solving and technical skills in support of research objectives. Scraping the required companies data from various sources and finding similarities using fuzzywuzzy library. Evaluated and assessed student performance in CIS-370 (Business Analytics) course, employing robust grading methodologies to measure comprehension and application of course materials. Provided constructive feedback to foster continuous learning and development, contributing to the enhancement of student skills and knowledge in business analytics and intelligence. Provided individualised tutoring and mentorship to students across multiple courses within the CIS (Computer Information Systems) department, offering guidance and support in comprehension and application of course materials. Leveraged strong communication and teaching skills to facilitate student learning and promote academic success Technologies used: Python,Java, NLP, JMP software, Business Analytics, MS Excel
Volunteer
AI Community
January 2019 - Present
- Profile: Machine Learning Engineer Project: Early Cancer Detection in Adults (Medical Science) Responsibilities: Implemented blockchain and artificial intelligence technologies to develop a platform facilitating early cancer detection in adults, with a specific focus on the youth age group. Collaborated with a multidisciplinary team to create a system connecting patients and healthcare providers with on-demand fellowship-trained expert radiologists globally. Utilised AI algorithms to assess the likelihood and risk of developing cancer based on patient symptoms, leveraging a comprehensive database of diseases and past symptoms. Employed feature engineering that led to the creation of a robust dataset comprising 1,000 features, ensuring data integrity and relevance. Developed and implemented an initial-level model based on patient symptoms, contributing to early cancer detection efforts. Collaborated with stakeholders to continuously refine and improve the platform's functionality and performance. Technologies used: Python, Blockchain Project: Natural Language Processing (NLP) and Sentiment Analysis Project Responsibilities: Conducted sentiment analysis on youth sentiments by web scraping data from Twitter, Instagram, and UNICEF, utilising Python. Performed Exploratory Data Analysis (EDA) to uncover patterns and distributions in the collected data. Employed advanced visualisation techniques using Plotly to create interactive basemaps, word clouds, violin plots, scatter plots, and dynamic heatmaps, facilitating deeper understanding of youth thoughts and sentiments. Visualised sentiment data over geographic locations using Tableau to provide insights into regional sentiment variations. Utilised Latent Dirichlet Allocation (LDA) to identify key topics in the data, revealing prevalent themes in youth sentiments. Technologies used: Python (NumPy, pandas, scikit-learn, TensorFlow, PyTorch), Plotly, Tableau, Latent Dirichlet Allocation (LDA), AWS Sagemaker
Education
Colorado State University Fort Collins
Master in Computer Information Systems
January 2023 - May 2024
IIIT
Master in Information Technology
September 2020 - June 2022
