Data Scientist - ML Engineer with Practical AI Skills

Nagpur, Maharashtra [******]

Summary

Kevin Divyansh Peter

+91-702-***-**** *************@*****.*** https://linkedin.com/in/kevin-peter-6418aa205/ Motivated Data Science Graduate with hands-on experience building machine learning models and analyzing complex datasets. Proficient in Python, SQL, and key AI/ML tools, with proven project successes—improving model precision and developing interactive dashboards. Eager to apply academic knowledge and practical skills to drive data-driven solutions as a AI/ML Engineer. Education

GH Raisoni Institute of Engineering and Technology Sep 2020 - Jul 2024 Bachelor of Technology, Data Science

Hislop College Jun 2019 - Mar 2020

High School Diploma

WorkExperience

Nullclass Edtech Data Science Developer Intern Dec 2023 - Jul 2024

• Developed an emotion detection system using live data streams, applying data preprocessing techniques to enhance model performance.

• Enhanced project functionality by integrating voice analysis, age prediction, and real-time audio-video analysis, leveraging feature engineering and data analysis skills.

Clustor Computing Data Science Developer Intern Dec 2022 - Jun 2023

• Conducted model analysis that achieved 76% accuracy through effective data-oriented programming.

• Implemented time series forecasting techniques to predict booking trends with 84% precision, utilizing statistical software for compre- hensive evaluation.

• Created interactive dashboards with Power BI to support data-driven decision making. Personifwy Data Science Intern Jun 2022 - Sep 2022

• Designed a chatbot prototype using Dialogue Flow, achieving 82% accuracy through systematic data preprocessing and model evaluation.

• Executed hierarchical clustering and linear discriminant analysis to extract actionable insights and reduce the error rate by 5%. Corizo Data Science Intern Jun 2022 - Aug 2022

• Engineered a machine learning model for road lane detection to mitigate accidents with 86% accuracy and 74% precision.

• Developed an image processing model for retinopathy detection, applying deep learning techniques to achieve 72% accuracy. Skill Vertex Data Science Intern Aug 2021 - Oct 2021

• Utilized data visualization tools to create interactive graphical representations of financial data for the stock market.

• Developed a predictive model for future house prices using historical data, achieving 68% precision in forecasting.

• Collaborated with team members to identify and resolve data-related issues, improving data accuracy by 86% through thorough data preprocessing.

Projects

Helmet and Number Plate Detection and Recognition

• Used YOLO v5 model to capture instances of images in which a bike rider who hasn't put on any helmet while driving.

• This model captures the riders along with their number plate and their faces.

• Have a future plan to enhance this project by creating a live detection and person identification using a sample data. Voice Gender Prediction

• Used RNN model in this project as it can help to capture sequential dependencies and temporal patterns in audio data.

• Used Librosa and pyAudioas libraries because of their features that can help in performing various voice related actions such as voice recording, playing audio and extracting features from audio signals.

• Achieved 88% of precision during the training of the dataset. Real-Time Sentiment Analysis

• Utilized multiple models like CNN, Deep Face, Keras, TensorFlow, Image processing.

• Built multiple sample working models either collaborated or individually with each of them having different specific purpose. Chatbot Development

• Developing an intelligent chatbot using JarvisAI, implementing natural language processing (NLP) techniques to handle user inquiries. Recommendation System

• Created a collaborative filtering recommender system using the MovieLens dataset, achieving an accuracy of 85% in predicting user preferences.

Road Sign Detection

• Utilized PyQt5, Image Processing, Keras to train, test and validate the model.

• Trained the model to detect 43 different Road Signs.

• The model has a Training accuracy of 87% and Validation accuracy of 93%. Facial Attendance Recognition

• Used OpenCV DNN, Torch, Pickle.

• The aim of the project is to automate attendance by detecting faces from images, extracting embeddings, and linking them to student identities.

Climate Prediction

• Used Keras, NumPy, Pandas, Matplotlib, Scikit-learn.

• The aim of this project is to enhance climate data prediction and synthesis by combining Bi-LSTM and GAN. Core Skills

• Technical Skills: Pandas, Numpy, Scikit-learn, SQL (MySQL), R Programming, GitHub, Git, Stream lit, Tensorflow, Machine Learning, Deep Learning, Power BI, Tableau, Excel, Tkinter, Prompt Engineering, Object Detection using OpenCV, YOLO, Gen AI, LLM, Langchain, Data Analysis, Data Preprocessing, Data-Oriented Programming, Feature Engineering, Model Evaluation, DeepSeek, OpenAI, Claude

• Interests: AR/VR, Music, Deep Learning and LLM functionality, Artificial Intelligence, Visualizations and dashboard Certificates

• Learn Artificial Intelligence & Machine Learning with Hands-On Projects Certificate (Udemy)

• Learn Artificial Intelligence & Machine Learning with Hands-On Projects Certificate (Udemy)

• Mastering AI Innovation Building and Fine-tuning Generative AI Applications with Google Gemini Models And Langchain

(Udemy)

• The Data Engineer's Guide to Apache Spark (Udemy)

• No-Code Machine Learning Using Amazon AWS SageMaker Canvas (Udemy)

• Get Started with SQL Analytics and BI on Databricks (Simpli Learn)

• Introduction to Diffusion Models (Simpli Learn)

• Introduction to GAN (Simpli Learn)

• Introduction to Tableau (Simpli Learn)

• Master AI for Web App Development (Simpli Learn)

• Get Started with Databricks for Machine Learning (Simpli Learn)

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