Hello & Welcome

I Am A Data

Saikrishna Paila

An eloquent tale of my journey

Hi đź‘‹, I'm Saikrishna Paila, an accomplished data science professional with a Master's degree in Data Science from The George Washington University. I am adept in leveraging advanced analytical techniques, including predictive modeling, machine learning, and natural language processing, to uncover meaningful patterns and trends within complex datasets. I have a proven track record in credit card churn analysis, supply chain management database optimization, and retail analytics for subscription insights, achieving high prediction accuracy through robust data preparation and model tuning.

  • Age: 22
  • Degree: Masters
6

Languages

8

Tools

1

Certificates

12

Projects

Skills I've Developed and Mastered

With a solid foundation in Data Science and Computer Science, I specialize in merging technical expertise with business insights to develop solutions that drive significant competitive advantages across various sectors.

  • Advanced Data Analytics and Visualization
  • Machine Learning and Predictive Modeling
  • Deep Learning Algorithms
  • Large Language Model
Profile Image
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Work Experience

Aug 2024 – Present

GWU logo
Graduate Instructional Assistant – Data Science Capstone, Columbian College of Arts and Sciences, The George Washington University, Washington, D.C., USA

Guided undergraduate students in the Data Science Capstone course, assisting with data extraction, preprocessing, and analysis to develop comprehensive final-year projects.

Led discussions on project strategy, model evaluation, and data visualization, enhancing students’ abilities to communicate findings effectively and adhere to data science best practices.

Education

Anticipated May 2025

GWU logo
Master of Science, Data Science, The George Washington University, Washington DC.

Relevant Coursework: Data Mining, Data Warehousing, Visualization of Complex Data, Machine Learning, Cloud Computing, Algorithm Design, NLP for Data Science, Linux for DevOps, Foundational Pedagogy GradAsst.

Jun 2019 - Jul 2023

Amrita logo
Bachelor of Technology, Computer Science, Amrita Vishwa Vidyapeetham, India.

Relevant Coursework: Natural Language Processing, Machine Learning, Distributed Systems, DBMS, Time Series Analysis, Mining of Massive Datasets, Social Network Analysis.

Projects

AI Meets Law
AI Meets Law: Transforming Legal Research

Integrated Retrieval-Augmented Generation (RAG) and fine-tuned LLMs for efficient legal research, featuring a user-friendly Streamlit interface.

Text Classification SciBERT
Text Classification Using SciBERT

Implemented multi-label classification with SciBERT, leveraging LSTM, CNN, and Fully Connected layers for scientific text categorization.

Python logo
Data-Driven Insights for Apple Stock Market Predictions

Developed robust time-series forecasting models, including LSTM with XGBoost and Voting Regressor, and enhanced ARIMA models.

Tableau
Advanced Data Visualization of Los Angeles Crime Patterns

Developed and optimized a data visualization platform for analyzing Los Angeles crime trends using Tableau and Python.

R logo
Credit Card Churn Analysis: Predictive Modeling for Customer Retention

Developed a churn prediction model using Random Forest, Logistic Regression, and Decision Tree algorithms.

MySQL logo MongoDB logo Neo4j logo
Supply Chain Management Database Efficiency Analysis

Investigated the efficiency of MySQL, MongoDB, and Neo4j in supply chain management by benchmarking their performance.

Languages & Tools

Python
90%
R
79%
Tableau
80%
MySQL
75%
MongoDB
70%
Neo4j
90%
// Languages function listLanguages() { let languages = [ "C++", "Python", "R", "SQL", "NoSQL" ]; console.log(languages); }
// Clouds function listClouds() { let clouds = [ "Amazon Web Services (AWS)", "Google Cloud Platform (GCP)", "Microsoft Azure" ]; console.log(clouds); }
// NLP and LLMs function listNLPandLLMs() { let nlpAndLLMs = [ "Large Language Models (LLMs)", "SentenceTransformers", "Sentence-BERT", "FAISS", "NLTK" ]; console.log(nlpAndLLMs); }
// Machine Learning Algorithms function listMLAlgorithms() { let mlAlgorithms = [ "Linear Regression", "Logistic Regression", "Decision Trees", "Random Forest", "XGBoost", "LSTM", "ARIMA", "SVM" ]; console.log(mlAlgorithms); }
// Frameworks function listFrameworks() { let frameworks = [ "Spark", "Kafka", "Hive", "Docker", "MongoDB", "HBase", "HDFS", "EC2", "S3", "Hadoop", "Apache", "LangChain", "Streamlit" ]; console.log(frameworks); }
// Softwares & Tools function listTools() { let tools = [ "Tableau", "PowerBI", "OpenCV", "SAS", "Excel", "TensorFlow", "Numpy", "Pandas", "Matplotlib", "PyTorch", "Scikit-learn", "Keras", "Scapy", "NLTK" ]; console.log(tools); }

Portfolio

See My Awesome Work
AskLaw Legal Assistant

AI Meets Law: Transforming Legal Research with RAG and Fine-Tuned LLM

Abstract: Integrated RAG and fine-tuned LLMs for efficient and precise legal research.
Tools & Technologies Used: Python, Streamlit, FAISS, GPT fine-tuning, SentenceTransformer
Conclusion: Delivered an AI solution for precise legal research with user-friendly interaction.

Text Classification Using SciBERT

Text Classification Using SciBERT

Abstract: Multi-label text classification with SciBERT and a multi-head architecture for scientific abstracts.
Tools & Technologies Used: Python, SciBERT, PyTorch, LSTM, CNN
Conclusion: Delivered a high-performing text classifier leveraging SciBERT and innovative deep learning techniques.

Apple Stock Market Predictions

Data-Driven Insights for Apple Stock Market Predictions

Abstract: Developed time-series forecasting models to analyze Apple Inc.'s stock data spanning nearly four decades.
Tools & Algorithms Used: Python, LSTM, XGBoost, Voting Regressor, ARIMA
Conclusion: Improved accuracy in stock predictions through feature engineering, hyperparameter optimization, and ensemble techniques.

Los Angeles Crime Patterns

Advanced Data Visualization of Los Angeles Crime Patterns

Abstract: Created a data visualization platform for analyzing Los Angeles crime trends using a 900K record dataset.
Tools Used: Tableau, Python
Conclusion: Enhanced law enforcement strategies through interactive dashboards highlighting key geographic and temporal patterns.

Credit Card Churn Analysis

Credit Card Churn analysis

Abstract: Developed a churn prediction model to enhance customer retention in the credit card industry.
Tools & Algorithms Used: R, Random Forest, Logistic Regression, Decision Tree
Conclusion: Significantly improved customer loyalty strategies through analysis of transaction data.

Supply Chain Management Database Efficiency Analysis

Supply Chain Management Database Efficiency Analysis

Abstract: Investigated the efficiency of various databases in supply chain management using DataCo's dataset.
Tools Used: MySQL, MongoDB, Neo4j
Conclusion: Optimized database selection for supply chain applications based on data retrieval speed and network pathfinding performance.

Customer Shopping Preference

Retail Analytics: Utilizing ML for Subscription Insights

Abstract: Predictive analytics framework using Random Forest and Neural Network models for Customer Shopping Preference analysis.
Tools & Algorithms Used: Python, Random Forest, Neural Network
Conclusion: Achieved 97% prediction accuracy in customer subscription behavior through advanced data normalization, categorical encoding, and hyperparameter optimization techniques.

Indoor Multi-Camera Human Tracking

Indoor Multi-Camera Human Tracking

Abstract: Developed a state-of-the-art multi-camera people detection and tracking system for indoor environments.
Tools Used: Python, OpenCV, TensorFlow, Keras
Conclusion: Achieved substantial performance improvements in open environments by successfully addressing occlusion challenges.

Achievement Hub

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Fine-Tune Your LLM

Through this course, I honed advanced skills in fine-tuning large language models to suit specific business and technical needs.

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RAG and Fine-Tuning Explained

This course enhanced my understanding of Retrieval-Augmented Generation (RAG) and fine-tuning techniques for LLMs, showcasing their practical applications.

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TensorFlow: Working with NLP

In this course, I acquired hands-on skills in TensorFlow for building natural language processing (NLP) models efficiently.

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GPT-4 Foundations: Building AI-Powered Apps

This course provided me with foundational knowledge to build AI-powered applications using GPT-4, focusing on software development and generative AI principles.

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Introduction to Generative AI with GPT

This achievement highlights my foundational knowledge in the principles of generative AI using GPT models, focusing on their capabilities and application scenarios.

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Generative AI: Working with Large Language Models

I gained advanced skills in large language models (LLM), natural language processing (NLP), and generative AI.

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Introduction to Prompt Engineering for Generative AI

I gained essential skills in natural language processing, generative AI & Prompt Engineering.

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Generative AI: Introduction to Large Language Models

I gained valuable insights into the architecture and applications of large language models and generative AI.

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Introduction to Large Language Models

I gained foundational knowledge in the architecture and functionality of large language models (LLMs).

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Customer Service Role at GW Commencement Day

I worked at the GW Commencement Day on June 19, 2024, where I played a key role in organizing and facilitating the event. My responsibilities included providing excellent customer service to graduates and guests, ensuring a smooth and memorable experience for everyone involved.

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Learning Design Thinking

I acquired advanced competencies in design thinking methodologies for the effective visualization and interpretation of complex datasets.

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Design Thinking: Prototyping

I acquired advanced competencies in design thinking methodologies and prototyping techniques.

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Student Athletic Assistant at George Washington University

This picture reflects my role as a Student Athletic Assistant at George Washington University, where I ensured excellent guest services and resolved attendee concerns at basketball events.

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DataCamp Intermediate SQL

This certification from DataCamp affirms my intermediate skills in SQL, focusing on complex queries and database manipulation for data analysis.

GitHub

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