Hi, I'm Yash Raj Bista
Data Science and Computational Intelligence Student
A Computer Engineer and an Oracle Database Administrator at World Distribution Nepal , Kathmandu, Nepal.
Contact meAbout Me
My introduction
I hold a Bachelor's degree in Computer Engineering from MIT-WPU and am currently pursuing my Master's in Data Science and Computational Intelligence at Softwarica College, affiliated with Coventry University, UK. Alongside my studies, I work as an Oracle Database Administrator, applying my skills in real-world enterprise environments. I’m passionate about technology, eager to learn, and constantly seek opportunities to expand my knowledge and stay ahead in the evolving tech landscape. With a proactive mindset and a can-do attitude, I thrive in dynamic and challenging environments. I'm looking to contribute to a forward-thinking organization where I can grow professionally while adding real value.
experience
Skills
My technical levelProgramming Languages
C
C++
Java
IT Constructs
DBMS
DS & Algorithms
OOP
OS
Technologies
Git
Oracle DB 11g
Oracle DB 12c
Oracle DB 19c
MySQL
PL/SQL
Experience
Clients I've worked with
Nepal Telecom
Managed Oracle 11g and 19c RAC clustered databases, ensuring high availability and optimal performance.
Performed RMAN backups, database switchover operations, and recovery procedures as part of the disaster recovery strategy.
Monitored Oracle Data Guard configurations for log transport and apply services to maintain synchronization between primary and standby databases.
Monitored tablespaces and ASM diskgroups, and proactively extended them when utilization exceeded 80%.
Troubleshot and resolved database-related issues to ensure smooth operation of critical services.
Generated monthly database health check reports and contributed to system performance reviews.
NCELL
Supported infrastructure modernization by migrating 1000+ VMs from VMware to Oracle PCA and OLVM.
Executed Oracle database migrations using Rackware RMM with zero data loss and minimal downtime.
Validated and tuned RAC and standalone databases post-migration to ensure stability and performance.
Documented migration SOPs and coordinated cutovers under strict SLAs and change controls.
Provided on-call production support and contributed to post-migration reviews.
DG-HUB
Monitored Oracle container databases (CDBs) with multiple pluggable databases (PDBs) to ensure smooth operation and resource optimization.
Conducted regular health checks and tracked performance metrics across all environments.
Generated and submitted database health reports for system audits and monitoring.
Himalayan Bank
Monitored multiple databases hosted on a single server, ensuring high availability and performance.
Oversaw Data Guard configurations and ensured synchronization for critical card systems.
Generated monthly health reports for all monitored databases to support audit and compliance.
Nepal Police
Monitored container database (CDB) environments with multiple pluggable databases (PDBs), including Traffic and NOC databases.
Ensured availability and performance of mission-critical systems through regular health checks and performance reviews.
Generated monthly health reports to support operational continuity and database maintenance planning.
Qualification
My personal journeyNEB (11th & 12th)
United AcademyHigh School
Bachelors
B.Tech in CSEMIT WPU, Pune
Masters
Softwarica College of IT and E-Commerce, KathmanduProjects
Most recent work
VerticalIR: Intelligent Vertical Search & Document Clustering System
VerticalIR is a two-part system that leverages natural language processing and machine learning to enhance academic information retrieval. The project combines a custom-built vertical search engine with a document clustering system to provide fast, topic-aware access to scholarly content. The vertical search engine uses a Python-based web crawler to scrape, extract, and index research publications from Coventry University's School of Computing. An inverted index structure supports efficient search, and a GUI enables intuitive interaction with search results in real time. The second component uses TF-IDF, K-Means, and Decision Trees to automatically cluster and classify documents into topics like Politics, Entertainment, and Economics. This includes full preprocessing (tokenization, lemmatization), real-time classification through a GUI, and performance evaluation using precision, recall, and F1-score. VerticalIR showcases the fusion of web crawling, indexing, unsupervised learning, and user-centric design to deliver intelligent and efficient document discovery and classification.
GitHub Repository
Gold Price Forecasting using LSTM Networks
Gold Price Forecasting using LSTM is a deep learning–based time-series prediction project aimed at accurately forecasting future gold prices. The project applies Long Short-Term Memory (LSTM) networks, a type of Recurrent Neural Network (RNN), to capture long-term temporal patterns and complex nonlinear trends in gold market data. The model is trained on a decade of historical gold price data (2013–2023) including attributes like open, close, high, low prices, trading volume, and daily percentage changes. Data preprocessing steps include normalization, sequence generation using a sliding window approach, and handling of missing values. The architecture features stacked LSTM layers with dropout for regularization and dense output layers. It is optimized using the Adam algorithm and evaluated through performance metrics such as RMSE, MAE, and R² Score. Visualization tools are used to compare predicted and actual prices, showcasing the model’s accuracy and trend alignment. This project highlights the superiority of LSTM over traditional models (like ARIMA and SVM) in modeling volatile financial data. Future improvements include integrating macroeconomic indicators and exploring Transformer-based architectures for even greater forecasting accuracy.
GitHub Repository