Pratyush Srivastava | Data Scientist

Hi, I'm Pratyush Srivastava.

A Data Sc|

Self-driven and highly motivated Data Scientist with a curious mind, passionate about Machine Learning, NLP, and Data Analytics. Enjoys solving complex real-world problems through data-driven approaches and AI-powered solutions.

About

A Data Scientist and Machine Learning Enthusiast with a passion for NLP, Deep Learning, and Data-Driven Solutions.

I am a Computer Science Graduate Student at Galgotias University with a deep passion for Data Science, Machine Learning, and NLP. With 3+ years of professional experience, I have honed my expertise in Python, Machine Learning, Deep Learning, NLP, and Data Analytics. My journey has involved working extensively on data preprocessing, model development, and deployment, along with technologies like Flask, MySQL, PostgreSQL, and cloud platforms.

As a detail-oriented Data Scientist and Machine Learning Engineer, I specialize in building intelligent, scalable solutions that solve complex real-world problems. I have hands-on experience in Natural Language Processing (NLP), Generative AI, Machine Learning and Deep Learning, and I am particularly passionate about leveraging AI to extract insights from unstructured data, develop predictive models, and deploy AI-driven applications.

I am actively seeking opportunities to apply my skills in data-driven problem-solving, model development, and analytics in a challenging role. I am eager to contribute to innovative projects while continuously learning and growing in the field of AI and Data Science.

Languages: Python, C, SQL (MySQL, PostgreSQL), HTML
Cloud Technologies: Google Cloud Platform (GCP), AWS, Heroku
Developer Tools: Git, VS Code, PyCharm, IntelliJ, Eclipse, Anaconda
Libraries and Frameworks: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras, NLTK, Langchain
Software Tools: MS Word, PowerPoint, MS Excel, Power BI
Technologies: Data Analysis, Machine Learning, NLP, Deep Learning, Data Engineering, Web Scraping, Model Deployment, Cloud Computing
Other Skills : Business Analytics, Data-Driven Decision Making, Statistical Analysis, Customer Insights, Predictive Modeling

Current Focus: Python / Machine Learning / Deep Learning / Data Science / Gen AI / Agentic AI

Experience

Infosys

Digital Specialist Engineer(Analytics)

Collaborated with cross-functional teams to define project requirements, ensuring AI solutions and analytics meet organizational goals.
Partnered with project managers to identify analytics needs, establish critical metrics and KPIs, and provide actionable insights to drive informed decision-making.
Designed, developed, and optimized generative AI models to improve performance, scalability, and efficiency in alignment with business objectives.
Developed and maintained AI and data pipelines, handling data preprocessing, feature extraction, model training, and evaluation to ensure efficient data flow.
Use Artificial Intelligence, NLP technologies, and cognitive machine learning to develop AI Applications.
Design and implement processes and strategies to enhance the end-user experience.
Contributed to the development of best practices for generative AI and data systems, troubleshooting and debugging issues while embracing new technologies to enhance analytical outcomes.
Tools: Python (Core & Advanced), Machine Learning & Deep Learning , Exploratory Data Analysis (EDA) , Flask , Generative AI , RAG , NLP

July 2022 - Present | Chandigarh, India

Professional Projects

LGE US Sales and Site Analytics Assistant

Collaborated with clients to gather requirements and design a highly efficient sales analytics chatbot solution, leveraging natural language processing (NLP) for enhanced user interaction.
Integrated the chatbot with Vertex AI, Gemini LLM model, and BigQuery, enabling real-time data processing, analysis, and actionable insights.
Designed and developed a robust query framework to construct and execute SQL queries, streamlining data retrieval and improving user insights through automated summarization.
Implemented an NLP pipeline to extract and map user entities, increasing accuracy in query interpretation and conversational responses.
Converted user queries into SQL statements, transforming data into natural language insights and delivering dynamic visualizations to enhance decision-making in a conversational format.
Tools: Python , NLP , SQL , VertexAI , BigQuery , GCP , Langchain

Home Seller Assistant

Leveraged large language models (LLMs) to develop a scalable solution for automating data extraction from mortgage documents within an AWS cloud environment.
Implemented a Retrieval-Augmented Generation (RAG) approach to classify and extract relevant information from mortgage document streams, streamlining the data population process into the user interface (UI).
Developed a Conversational AI solution, incorporating a document QnA chatbot powered by enterprise-grade vector databases and document embeddings using LangChain, delivering an efficient and intelligent document processing workflow.
Tools: Python , Large Language Models(LLMs) , RAG , LangChain , AWS

Personal Projects

                
Air Assult Game
                  An Arcade Game based on PyGame(Python)
                
AccomplishmentsThe Air Assult Game is a dynamic and challenging game where players control a copter flying through an obstacle-filled path. As soon as the game starts, the copter automatically moves forward, and the player’s goal is to balance it by navigating around obstacles to avoid crashes. The difficulty increases as the game progresses, keeping players on their toes. Developed using Python, Tkinter, and PyGame, the game provides a smooth, addictive, and engaging experience.

Rain Prediction App
                  A Rain Prediction Machine Learning App
                
AccomplishmentsThis project involves the development of a Weather Prediction Model that forecasts whether the next day will be sunny or rainy. Using machine learning algorithms, the model analyzes historical weather data to make accurate predictions. It was built using Python, along with data manipulation libraries such as Pandas and NumPy, and trained using ScikitLearn. The model was then deployed on the Heroku Cloud Server, ensuring it is accessible online for real-time predictions. This project demonstrates my proficiency in machine learning, data processing, and cloud deployment.

Attendence Management System
                  A Simple and Extensible Desktop Application Based on OpenCv.
                
AccomplishmentsThis is a Student Attendance Management System, a desktop application designed to automatically detect and track student attendance using facial recognition technology. The system leverages OpenCV for real-time image processing and machine learning algorithms to identify students and mark their attendance accurately. Attendance records are stored and managed using Excel sheets, making it easy to maintain and update student data. Built with Python and Tkinter, the application provides an intuitive user interface, offering seamless integration of machine learning and image processing techniques.

Mushroom Prediction Model
                  A Mushroom Prediction Machine Learning App
                
Accomplishments
                    This project involves a Mushroom Classification Model that predicts whether a mushroom is poisonous or not based on various features such as its color, size, and shape. Using machine learning classification algorithms, the model analyzes the provided attributes and classifies the mushroom as either edible or toxic. The model has been deployed on Streamlit, providing an interactive and user-friendly web interface for real-time predictions. This project demonstrates my expertise in machine learning, data classification, and web deployment.
                  
Blood Bank Management System
                  A Web app Based on Django
                
AccomplishmentsThe Blood Bank Management System is a web-based platform designed to streamline and automate the process of managing blood donations, recipients, and stocks. The system simplifies the search for blood during emergencies and helps in maintaining a detailed record of blood donors, donation events, and available blood units in the bank. Built with Django for the backend and SQLite for the database, the platform features an intuitive user interface created using HTML, CSS, and Bootstrap, with interactive elements powered by JavaScript. This project showcases my skills in web development, database management, and creating solutions to address real-world problems.

Uber Ride Prediction
                  An Uber Ride Prediction Machine Learning Web App
                
Accomplishments The Ride Prediction System is a machine learning web application designed to predict the number of rides a user will take per month. By analyzing historical data, the model forecasts monthly ride usage based on various features. The application is built using Flask, enabling a smooth integration of the machine learning model with a user-friendly web interface. The frontend is developed with HTML, CSS, and JavaScript to provide an interactive experience, while the machine learning model predicts ride patterns. The application has been deployed on Heroku, making it accessible for real-time predictions. This project demonstrates my expertise in machine learning, web development, and cloud deployment.

Skills

Programming Languages

Python

HTML5

SQL

C

Core Java

Databases

MySQL

PostgreSQL

MongoDB

Libraries

NumPy

Pandas

OpenCV

scikit-learn

matplotlib

Streamlit

Frameworks

Lang Chain

Keras

TensorFlow

Flask

Other

Git

AWS

Heroku

GCP

MS Excel

Power Bi

Education

                  Galgotias University
                
Greater Noida, Uttar Pradesh, India

                  Degree: Bachelor of Technology in Computer Science and Engineering
                  
                  CGPA: 8.78/10.0
                  
                  Batch: 2018-2022
                
                    Relevant Courseworks:
                  
                      Database Management System
Operating System
Compiler Design
Design and Analysis of Algorithms
Software Engineering and Testing Methodologies

                  Green Field Academy
                
Lakhimpur Kheri, Uttar Pradesh, India

                  Degree: Intermediate(12th)
                  
                  Percentage: 84.8%
                  
                  Batch: 2016-2018
                
                    Relevant Courseworks:
                  
Physics
Chemistry
Mathematics
English
Hindi

                  Green Field Academy
                
Lakhimpur Kheri, Uttar Pradesh, India

                Degree: HighSchool(10th)
                
                CGPA: 10.0/10.0
                
                Batch: 2014-2016
              
                    Relevant Courseworks:
                  
Social Science
Science
Mathematics
English
Hindi

Certifications and Achievements

All India Rank 6 in National Engineering Olympiad 2021(NEO 4.0) in the Category of Computer Science and Engineering

Finalist of Ami-Techfiesta 2020(A Programming Challenge)

Cleared HackwithInfy All India Coding Contest of Infosys in 2021.

Cleared AMCAT EXAM with A Grade in Computer Science

Microsoft Azure AI Fundamentals Certified

Microsoft Technology Associate(MTA) Certified in Python Programming

Infosys Certified Python Programmer

Infosys Certified Python Associate

Hackerrank Certification in Python(Basics) and Problem Solving Basics

Infosys Certified Java SE11 Developer

Research Paper and Publications

Research Paper : Attendence Management System Using OpenCV : Published in n 3rd IEEE International Conference(Scopus) on Advances in Computing, Communication Control and Networking on (March 2022)

Research Paper : Food Calorie Prediction Using MobileNet: Selected in International Conference on Advance Research and Innovation (ICARI-2022)

Resume

Contact

pratyushsrivastava500@gmail.com

GitHub

Noida Uttar Pradesh , India

Prepared By Pratyush Srivastava