Sachin Jain

About Me

I like solving real problems, especially the kind where data science, business decisions, and human behavior collide.

I recently completed my Master's in Artificial Intelligence and Business Analytics, where I focused on using machine learning and modern analytics to build smarter systems and make decisions that actually move the needle. My background is in Computer Science and Data Science, but my curiosity often pulls me toward Psychology and Neuroscience. I am especially interested in how people think, where their biases hide, and how we can design AI to work with that complexity instead of against it.

I enjoy turning messy data into clear insights using tools like Python, SQL, and Tableau. I am most excited when those insights lead to better decisions, stronger products, or smarter strategies. Whether it is building predictive models, automating processes, or making sense of unstructured information, I care about creating solutions that actually help.

I have worked in startups, academia, and corporate teams. What I have learned is simple. Clear thinking wins. Iteration compounds. And no model beats a well-posed question. I care about building things that work, making things better than they were, and doing it with people who care just as much.

Outside of work, I enjoy meaningful conversations, learning from people, and exploring new places. Lately, I have been loving surfing through the AI wave, exploring every new tool, and adding them to my tech stack along the way. I like following my curiosity, whether it leads to a new project, a good book, or an unexpected idea.

I am currently looking for full-time roles in Business Analytics, Data Science, or Business Intelligence where I can contribute, learn, and solve meaningful problems. If something here resonates or you are working on challenges worth exploring, I would love to connect.

Work Experience

Projects and Technical Skills

Streamlining Data Processing Pipelines for Large-scale E-commerce Platform

Spearheaded the development of a hybrid analytical framework for an e-commerce platform, integrating real-time and offline analysis with advanced machine learning models, predicting user behavior insights and purchase analytics.
Implemented Locality Sensitive Hashing (LSH) in MongoDB for batch processing to identify similar users and utilized machine learning models like Random Forest, XGBoost, and ANN to predict purchase likelihood.

Text Summarization with Large Language Models

Performed extensive experiments on CNN/Daily Mail and EdinburghNLP/XSum datasets for significant improvements in summarization quality using MPT-7b-instruct, Falcon-7b-instruct, OpenAI's ChatGPT text-davinci-003, and BERT.
Rated the performance of LLMs by comparing their ROUGE, BERT precision, recall, F1 metrics, and BLEU scores.

LinkedIn Job Insights: Analytical Exploration for Career Trends

Data-driven Customer Segmentation and Targeted Marketing

Portfolio Website | HTML, CSS, Javascript

Skills