About Me

Hi, I’m Prajwal — born and raised in Bangalore and now building my career in the world of data and AI. I have recently earned my Master’s in Business Analytics & Artificial Intelligence at UT Dallas.

1️⃣ Right now, I work at Albertsons as a Data Engineer, where I build data pipelines and tools that make financial processes like Profit & Loss allocation more efficient and reliable. Before this, I worked at GenerativeProduct.io, where I explored the practical side of Generative AI, from RAG systems to agentic AI. I enjoy working at the intersection of data engineering and applied AI — solving problems end to end, from moving raw data to delivering something that creates impact.

2️⃣ 2 – Outside of work (hobbies & interests): Outside of work, I’ve recently gotten back into cycling, aiming for 8–10 miles per ride as I rebuild consistency. I’m also planning to try candle-making soon as a creative side hobby. I love playing FIFA, watching Manchester United, and mixing football stats with my love for the game. When I’m not on the bike or gaming, I’m usually catching up on tech trends, news, and current affairs, or just exploring new hobbies that let me recharge and stay curious.

Contact me at prajwalkp.work@gmail.com

What I'm Currently Learning

Generative AI

I'm currently diving deeper into generative AI and large language models, exploring how they can transform business intelligence and analytics.

Cloud Data & Analytics

Exploring Microsoft Synapse Analytics and Azure services to build scalable data solutions, optimize analytics workflows, and enhance cloud-based data processing.

My Skills

Languages

Python, R SQL and VectorDB - FAISS, Pinecone SAS Bash/Shell Scripting

Tools

Data Viz - Tableau, Looker and PowerBI Databricks Snowflake Docker & Kubernetes Git, GitLab and Azure Repos Jira & Confluence Apache Kafka, Airflow, Spark, dbt Hadoop

Cloud

Azure: Synapse Analytics, DevOps AWS: EC2, S3, QuickSight

Machine Learning and AI

Scikit-Learn Tensorflow PyTorch LangChain & LLamaIndex

Libraries

Numpy, Pandas, Matplotlib Plotly & Seaborn Flask & Streamlit

Resume and Experience

Access my CV in pdf format HERE.

Experience

Data Engineer I

July 2025 — Current
At Albertsons Companies, Inc

Product Data Scientist

July 2024 — July 2025
At GenerativeProducts

R&D Data Engineer

July 2022 — July 2023
At ABB India

Data Scientist Intern

June 2021 — July 2022
At ABB India

Education

The University of Texas At Dallas

Master of Science, Business Analytics and Artificial Intelligence
August 2023 - May 2025

PES University - Bangalore, India

Bachelor of Technology, Electrical and Electronics Engineering and Minor in Computer Science
August 2018 - May 2022

Projects

Amazon Bookstore ETL Pipeline using Apache Airflow -[Link]

Built an automated ETL pipeline using Apache Airflow to extract book data directly from the Amazon Bookstore, transform it for consistency, and load it into a PostgreSQL database. This enabled structured analysis of titles, pricing, ratings, and availability for downstream insights.

CometVerse -[Link]

CometVerse is a voice-enabled AI chatbot built for UT Dallas, designed to handle student queries using LLMs and NLP. It supports conversation history, voice input, and PDF export, offering a smarter, more interactive alternative to traditional university chatbots.

LLM-Powered Product Management Interview System (PMInterviewAssistant) - [Link]

An AI-powered tool designed to help candidates prepare for Product Management interviews by providing automated real-time feedback. It leverages Speech-to-Text, Retrieval-Augmented Generation (RAG), and LLMs to enhance interview readiness and improve responses.

Advanced Analytics for Uber & Lyft Demand Prediction in Boston -[Link]

Developed a predictive model using ML techniques (Linear/Polynomial Regression, SVR, Decision Tree, Random Forest, etc.) to forecast ride demand. The project supports smarter driver allocation, pricing strategies, and overall efficiency in ride-hailing services.

Real-Time Event Streaming Pipeline with Kafka, BigQuery & PowerBI - [Link]

To build this, we will make usage of a popular distributed streaming platform Apache Kafka, to produce, consume and stream our data into BigQuery (data warehouse) so we can do some analysis using SQL and connect it to PowerBI where we are going to visualize on a dashboard.

NFL Injury Prediction (Logistic Regression & Decision Forest) - [Link]

The goal was to understand player injuries based on specific variables related to plays & game conditions. Apart from basic ML models, traditional survival analysis models were also explored - Cox Proportional Hazard model. Feature Importance using Mean Decrease in Impurity (MDI) was obtained.

Bengaluru Real Estate Prediction (EDA, Linear Regression) - [Link]

Presented important insights and built a model for the prediction of real estate prices in the city of Bengaluru. Got an accuracy score of 0.68 for the model used. Comparison of other models - Lasso and Decision Trees was also explored.

Prajwal P Kulkarni