Minneapolis, Minnesota, United States
Microsoft Certified Data Scientist with half a decade of experience delivering high-impact analytics solutions (Azure, Snowflake, Python, SQL, Power BI). Skilled at transforming complex data into actionable strategies through strong communication and business acumen. Proven ability to manage client relationships and deliver end-to-end data solutions from inception to completion in Advanced Analytics (AI/ML) and Business Intelligence (BI). Currently advancing AI/ML expertise via Georgia Tech’s top-5 nationally ranked Analytics Master’s program. 🎓 Education • Georgia Institute of Technology: Masters of Science in Analytics (Computational Data Analytics - AI/ML) • St. Olaf College: Bachelor of Arts in Mathematics & Economics with Concentration in Statistics & Data Science • Budhanilkantha School: Cambridge International GCE A-Levels in Physics, Chemistry, Mathematics, Economics, English 🤖🧠 AI & ML Platforms: Azure Machine Learning, Azure Databricks, VertexAI, MLflow, MLOps, Foundation Models, AI Agents, MCP • ML Models: Supervised - Regression (Regularized, Logistic), Decision Tree, Random Forest, SVMs, Naive Bayes, Gradient Boosting (XGBoost, LightGBM), Unsupervised - KNN, KMeans clustering, PCA • Deep Learning: CNNs, RNNs, Neural Network • NLP: LLMs, RAG, LAD, GPT, BERT, Perceptron, SVD, LSTM, Glove, Word2Vec (C-Bow, Skip-Gram) 🔗⚙️ Data Engineering and Management: Snowflake, Azure Data Factory, Azure Synapse Analytics, Azure SQL DBs, SQL Server, MYSQL, PostgreSQL, Azure CosmosDB, Big Query, Logic Apps, Docker 💻 Programing Languages: Python, SQL, R, Power Query, DAX, C#, C++ • Python Library: Numpy, Pandas, Scikit-learn, Tensorflow, Pytorch, NLTK, Seaborn, spaCy, Plotly • R Library: tidyverse, Shiny, FNN, glmnet, randomForest, tree, LakeMetabolizer, lubridate 📈📊 Data Visualization: Power BI, Tableau, Matplotlib, ggplot, D3.js, Excel, Google Data Studio, Graphana, New Relic 🐙🔄 Version Control and extra: GitHub, Azure DevOps, Microsoft 365, SharePoint, WordPress 🏅 Certifications: • Microsoft Certified: Azure Data Scientist Associate • Microsoft Certified: Data Analyst Associate • Snowflake: BUILD 2023 LLM Bootcamp Badge • The Dale Carnegie Course 🌍 Languages: Fluent in English, Nepali, Hindi ⚽ Hobby: Soccer (Playmaker 6, 8), Singing (YouTuber), Fishing (Bass and Brook Trout), Health & Fitness (Weight Lifting, Diet, Recovery), Hair Cutting (Fade), Drone Cinematography (DJI Mini 4 pro)
Independent Contractor Developing an enterprise-wide Business Intelligence and Advanced Data Analytics solution enabling the organization to gain strategic insights into its operations, broaden public outreach and engagement, and drive greater organizational impact in service of community health and equity.
🎓 Pursuing MS in Computational Data Analytics (AI | ML) at Georgia Institute of Technology (Top-5 Nationally ranked in Data Science and Analytics) ▪️Summer 2025 Courses: 👉 Deep Learning (Neural Networks, CNNs, RNNs, LSTM, NLP, Generative Models, Transformers, Embeddings, GANs, PyTorch, Reinforcement Learning) 🚀 Project: Deepfake Detection (Large Vision Models, PyTorch) 👉 Simulation 🚀 Project: Fast Food Simulation (Arena, Probability/Statistics) 👉 Data Analytics for Business (R) ▪️Spring 2025 Courses: 👉 Applied Natural Language Processing: (NLP, Neural Network, CNN, RNN, Transformers (GPT, BERT), LDA, Generative AI, Prompt Engineering, RAG, LLMs, cBoW, TF-IDF) 👉 Computational Data Analysis: (ML, Python - Spectral Clustering, PCA, Density Estimation, Gaussian Mixture Model, Optimization, Classification Naïve Bayes and Logistic Regression, SVM, Neural Networks, Anomaly Detection, Boosting Algorithms and AdaBoos, Random Forest) 🚀 Final Project: Data-Driven Prediction of FIFA Ballon d’Or (Men’s) Winner & Nominees • Developed Machine Learning models using real-world player statistics (FBref) to forecast 2025 FIFA Ballon d’Or outcomes, offering a data-driven alternative to traditional voting. Conducted data scraping, integration, and feature engineering; trained multiple ML models (Classification, Ranking), achieving a 98.3% ROC AUC score with stacked XGBoost and LightGBM 👉Data and Visual Analytics: (Python, OpenRefine, D3 Graphs & Tableau Viz, Spark, Docker, DataBricks, AWS, Hadoop, Pig, Hive, Spark, HBase, PageRank, Random Forest, Scikit-Learn, Project @ 50%) 🚀 Final Project: Impact Analysis of Weather & Holidays on NYC Subway Ridership • Performed data ingestion, processing, and built predictive and time-series models to forecast subway ridership based on weather and holiday, achieving 74.8% R-squared with Random Forest • Built and deployed model inferencing web app and interactive D3, Tableau visualizations to predict daily subway ridership
• Worked closely with clients (B2B) to understand their enterprise-level business problems and technology needs, and provided customized state-of-the-art Data Solutions to better streamline their data ecosystem in a wide range of disciplines such as Business Intelligence Analytics, Data Engineering & Warehousing, Database Storage & Management, and Machine Learning (ML) • Spearheaded the deployment of client’s local Text Classification ML models into production (GCP, AI Platform, Big Query, Cloud Run) by gathering the business requirements, reviewing the existing codebase (Python, SBERT, SpaCy), building robust ML pipelines using MLOps practices, and deploying in production, thus eliminating 30+ hours per week of manual model training inference processes and improving system reliability • Pioneered an end-to-end Power BI solution for a non-profit, automating data integration (CRM, webinars) via Dataflows and developing KPIs. Empowered executive leadership with data-driven insights to drive strategic decisions, driving a 10% expansion in public health reach and securing essential funding for business growth • Owned Azure Data Factory pipelines during a pivotal client personnel transition—resolving 11+ critical pipeline failures and securing code vulnerabilities to ensure 100% data integrity in Azure Dedicated SQL Pool, preventing operational downtime and safeguarding business continuity • Led data infrastructure modernization projects through Azure Cloud migrations (Azure SQL DB, Managed Instance, Data warehousing), optimized databases and servers for 15+ clients and internal systems; delivered monthly comprehensive DBA services —including performance tuning (indexes, query optimization, job scheduling) and agile BI/ETL pipeline support; future-proofed client's growing business and technology needs with better-streamlined data solutions and robust operational efficiency for profitable outcomes
• Contributed on building a Spiking Neural Network toolbox to study the complex adaptive system • Built stand alone programs to create input files and to visualize the outputs for the Neural Network toolbox using Python and R.