Data Scientist & ML Engineer
Building Intelligent Solutions
I transform complex data into actionable insights and build scalable machine learning models that drive real-world impact.
About Me
I am an enthusiastic Data Science professional currently pursuing a Master's in Data Science, Analytics, and Engineering at Arizona State University. My experience at Boeing has been instrumental in honing my skills in managing complex data ingestion pipelines and collaborating with diverse teams to deliver scalable solutions.
I'm proficient in Python, PySpark, and Databricks, and I'm truly passionate about using technology to foster sustainable innovation. I aim to apply my skills to tackle real-world challenges in data engineering and machine learning. My career journey showcases my dedication to efficiency, innovation, and making meaningful contributions that can truly make a difference!
Machine Learning
Developing predictive models and deep learning solutions.
Data Engineering
Building robust ETL pipelines and scalable data architectures.
Data Analytics
Turning numbers into compelling stories and dashboards.
Full Stack Data
End-to-end development from database to deployment.
Professional Journey
Data Science Intern
- Collaborated with global team to fix API bugs, prevent errors, and add security features for safer data handling
- Improved LLM accuracy by 8% by integrating structured deal context into prompts, increasing sentiment scoring precision, and delivering reliable Customer Relationship Management (CRM) insights for 100+ deals
Data Engineer
- Entrusted with managing and streamlining ingestion of obstacle data from 15+ global sources into Databricks, executing precise risk evaluations, and implementing workflows boosting data processing efficiency by 70%
- Directed a team of 3 engineers to create an automated ETL pipeline leveraging PySpark and Python, ensuring technical alignment and on-time milestone completion. The initiative reduced manual tasks by 85% and elevated data reliability
- Engineered a data pipeline in Databricks to process diverse obstacle data (CSV, PDF, XML) from multiple countries, automating manual entry and elevating operational efficiency by 80%
- Analyzed business performance data and communicated insights to cross-functional teams, addressing CRM-related challenges, boosting data accuracy by 20%, and aligning project requirements with business objectives
- Recognized with Boeing Recognition Award for processing complex PDF data with 99% accuracy, cutting down data extraction time by 90%
Cloud Intern
- Developed a serverless text transfer system with AWS Lambda and DynamoDB, enabling real-time data exchange, decreasing latency by 40%, and ensuring scalability for a cloud-based traffic platform
- Created a traffic management application with HTML, CSS, and JavaScript to alleviate congestion
Featured Projects
A showcase of my technical projects, ranging from machine learning models to full-stack web applications.
Adversarial Robustness Evaluation for LLMs
Built an adversarial robustness pipeline using PyTorch, Transformers, and Hugging Face to test GPT-2 on 600+ prompt-attack-defense scenarios, achieving 99.06% classifier accuracy.
Multivariate S&P 500 Forecasting Using News Sentiment and Global Indices
Engineered an LSTM forecasting model combining S&P 500, Nikkei, Hang Seng, Shanghai data with FinBERT sentiment to predict market trends.
Real-Time Phishing Detection using Graph Neural Networks (GNNs)
Developed a full-stack phishing detection system with GCN3, extracting lexical, domain, and HTML features for real-time browser protection.
Sustainable Innovation Web Application
Full-stack Next.js application promoting sustainable waste management using Google's Gemini AI for creative upcycling suggestions
Genre Odyssey: Film Visualization
Interactive D3.js visualization mapping relationships across genres, directors, and films
Adversarial Attacks on AI Models
CNN model to analyze the CIFAR-10 dataset
Oral Cancer Detection & Classification
DenseNet architecture achieving 95.24% accuracy in cancer classification
Bird Species Detection using CNN
CNN model for classifying bird species from audio recordings
Crop Price Prediction
Machine learning model for agricultural commodity price forecasting
Technical Proficiency
A comprehensive overview of my technical stack and areas of expertise.
Programming Languages
Tools & Frameworks
Cloud & Databases
Development Practices
Core Expertise
Community Impact
Giving back to the community through mentorship, leadership, and open source contributions.
Voter Awareness Campaign
Volunteered for a voter awareness campaign during the panchayat elections in several Jharkhand villages. Actively involved in informing, educating, and motivating citizens to exercise their right to vote, thereby contributing to the democratic process at the grassroots level.
Regenerative Restoring Planet Event
Nature's Orbit
Volunteered at Nature's Orbit for their Regenerative Restoring Planet event, organized in collaboration with NEHHDC (North Eastern Handicrafts & Handlooms Development Corporation Limited). Contributed to hosting a zero-waste event aimed at restoring and healing the planet.
Ironman 2025 Arizona Volunteer
Ironman
Volunteered at Ironman 2025 Arizona, assisting with athlete check-in and managing the run aid station to support athletes during the event.