Aniket Malpure

AI/ML Engineer | Data Scientist
Gainesville, US.

About

Highly skilled and results-oriented AI/ML and Data professional with a strong academic foundation (Masters in Applied Data Science, University of Florida) and practical experience in developing, deploying, and optimizing advanced machine learning models and data pipelines. Proven ability to drive significant improvements in data accuracy, operational efficiency, and user engagement across diverse domains including NLP, Computer Vision, and Data Engineering. Adept at leveraging cloud platforms (AWS, Azure) and MLOps practices to deliver robust, scalable solutions.

Work

Twister Lab, University of Florida
|

Graduate Research Assistant

Summary

Conducted research in Speech Emotion Recognition and Voice Analysis, leveraging state-of-the-art AI models to enhance productivity in academic environments.

Highlights

Pioneered a Speech Emotion Recognition and Voice Analysis System leveraging the state-of-the-art wav2vec2 model to accurately map emotions and empathy in classroom settings, significantly enhancing faculty productivity.

Engineered and deployed pre-trained Audeering and SpeechBrain models to extract critical voice features from over 20 faculty member audio responses, establishing a robust dataset and boosting emotional analysis accuracy by 5%.

Bajaj Finance Ltd.
|

Data Engineer

Summary

Led data engineering initiatives, focusing on advanced algorithm development, database architecture optimization, and automation of critical data workflows.

Highlights

Developed a Fuzzy Name Matching Algorithm utilizing 20 string similarity features and Deep LSTM Siamese networks, elevating customer identification accuracy by 11% (from 83% to 94%) across critical banking applications.

Architected a robust stacked Ensemble Model, integrating AutoML-optimized base classifiers with character embedding networks and Logistic Regression Meta-Models via Stratified 10-fold Cross-Validation, significantly reducing manual verification efforts in loan applications.

Modernized and optimized PostgreSQL database architecture for Product on Demand (EMI POD, Document POD, PartnerLending POD) platforms, resulting in a 30% improvement in response times and a 15% increase in operational efficiency.

Automated critical data workflows by designing and implementing ETL/ELT pipelines using Azure Data Factory for PostgreSQL, streamlining PowerBI reporting, reducing manual effort by 25%, and ensuring timely insight delivery.

Engineered and deployed CI/CD pipelines with Azure DevOps for PostgreSQL databases, integrating Azure Key Vault, Azure PowerShell, and Azure Repos to facilitate secure and efficient deployments.

Recognized with a Kudos award for excellence in maintaining comprehensive Confluence documentation, fostering enhanced team collaboration and project success.

Pune Institute of Computer Technology
|

Undergraduate Research Assistant

Summary

Contributed to research in deep learning applications for plant disease detection and model optimization.

Highlights

Developed a CNN-based Plant Disease Classifier, achieving high performance metrics: 95.62% accuracy, 94.38% precision, and 93.60% recall for robust disease detection.

Utilized transfer learning techniques with VGG19 and ResNet architectures to benchmark performance and optimize model accuracy for plant disease classification.

Babel Pte. Ltd.
|

Data Analyst Intern

Summary

Gained practical experience in sentiment analysis, recommendation system development, and database performance optimization.

Highlights

Performed advanced Sentiment Analysis using NLTK, VADER, and ROBERTa, identifying key behavioral patterns that led to a 15% increase in user engagement.

Engineered a sophisticated Recommendation System, integrating content-based and collaborative filtering with Graph Neural Networks (GNNs) for user-item relationship analysis, driving a 30% improvement in user engagement and content accuracy.

Optimized real-time SQL queries, significantly reducing execution time by 120ms and enhancing overall database performance to support improved decision-making.

Education

University of Florida

Masters

Applied Data Science

Grade: 4.0/4.0

Pune Institute of Computer Technology

Bachelors

Electronics and Telecommunications, Honors in AI ML

Grade: 8.98/10

Skills

Programming Languages

Python, C++, R, SQL, PostgreSQL, MySQL, Snowflake.

Machine Learning & Data Science

Scikit-learn, TensorFlow, Keras, PyTorch, Optimization, Neural Networks (CNNs, RNNs, LSTM, GRU), Transformers, Encoder-Decoder, Attention Mechanism, Statistical Modelling, Hypothesis Testing.

Natural Language Processing (NLP)

Hugging Face Transformers, NLTK, SpaCy, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), OpenAI API, Groq, Ollama.

Computer Vision & Robotics

YOLO (You Only Look Once), OpenCV, Roboflow, Object Detection, Object Tracking, Real-Time Inference.

Data Analysis & Visualization

Pandas, NumPy, Matplotlib, Seaborn, Exploratory Data Analysis, PowerBI.

Big Data & Cloud Platforms

AWS (S3, EC2, SageMaker), Azure (Data Factory, DevOps), Hadoop, Spark.

MLOps, Deployment & DevOps

Docker, Git, GitHub, Linux, Flask, Streamlit, Django, CI/CD, Azure DevOps, Azure Key Vault, Azure PowerShell, Azure Repos.

Projects

Football Analysis System with YOLO, OpenCV, and Python

Summary

Developed an advanced Football Analysis System leveraging YOLO, OpenCV, and Python for comprehensive player tracking, team assignment, and ball possession analysis, generating critical match insights.

AI/NLP TV Series Analysis System

Summary

Designed and deployed an end-to-end AI/NLP system using Scrapy, Hugging Face Transformers, and Gradio to automate theme extraction, genre classification, and enable sophisticated dialogue-based chatbot interactions for TV series analysis.