Hello, I am

Aryan.

2

GenAI Projects

2

Machine Learning Projects

1

Deep Learning Project

1

SQL Project

About Me

I’m a Data Science and Machine Learning Aspirant with hands-on experience building end-to-end AI solutions across FinTech, Retail, Healthcare, and E-commerce domains. My work focuses on turning data into actionable insights through well-designed machine learning models and scalable deployments.

I’m skilled in Python, SQL, Machine Learning, Deep Learning, and NLP, and I enjoy working across the full ML lifecycle—from exploratory data analysis and feature engineering to model deployment using Streamlit and FastAPI. I’ve built real-world projects involving computer vision, sentiment analysis, credit risk modeling, and recommendation systems, always with a strong emphasis on business impact and performance optimization.

Currently I am B.Tech Graduate in Computer Science, I’m continuously learning and experimenting with modern AI tools such as Transformers, RAG systems, and Generative AI, with the goal of building intelligent, user-centric products.

Key Skills

Programming & Development: Python, SQL, FastAPI, Streamlit, REST APIs, Git/GitHub

Data Science & Analytics: Data Analysis, Exploratory Data Analysis (EDA), Data Cleaning, Data Transformation, Feature Engineering, Statistical Analysis, Data Visualization

Machine Learning & AI: Predictive Modeling, Classification & Regression, Clustering, Ensemble Learning, Model Optimization, Deep Learning, CNNs, Transfer Learning, NLP

Generative AI & LLM Engineering: Prompt Engineering, RAG Applications, AI Agents, LangChain, LangGraph, Vector Databases, Agentic AI, LLM Fine-Tuning

Tools & Frameworks: NumPy, Pandas, Scikit-learn, PyTorch, Matplotlib, Seaborn, Hugging Face, ChromaDB, Jupyter Notebook, Google Colab

Core Concepts: Probability & Statistics, Hypothesis Testing, A/B Testing, Cross-Validation, Hyperparameter Tuning, Model Deployment & Monitoring

My Projects

My Experience

Data Science Intern

Atiq Technologies (Remote)
Aug 2025 – Dec 2025

I worked as a Data Science Intern where I designed and deployed end-to-end machine learning solutions across multiple real-world domains including healthcare, finance, and retail.

Built complete ML pipelines covering data cleaning, exploratory data analysis, feature engineering, model training, and deployment.
Improved model performance by 15–25% using advanced feature engineering, cross-validation, and hyperparameter tuning techniques.
Developed interactive ML web applications using Streamlit, enabling real-time predictions for over 100+ test users.
Deployed machine learning models using FastAPI REST APIs, reducing inference latency by approximately 30%.
Collaborated on industry-simulated projects following the full ML lifecycle, including documentation, version control, and result presentation.