Parimala Anjanappa
Data Science • AI/ML Engineer • Data Analysis • Software Engineering
Passionate about transforming data into actionable insights and building models that solve real-world problems. Currently seeking opportunities to make meaningful contributions in Data Science and AI.
About Me
My 'why' is rooted in a deep passion for this field and genuine curiosity to solve real-world problems through data and technology. I have masters in Applied data science from Indiana University and ~6 years experience working in IT on ML/ AI/ Data projetcs. I'm grateful for the opportunity to pursue work that challenges me intellectually and fulfills me personally.
I'm actively seeking opportunities to work on impactful projects as a Data Analyst, Data Engineer, or in AI/ML roles.
Technical Skills
Programming Languages
Data Engineering
Machine Learning & AI
Cloud & Databases
Data Visualization
Featured Projects
🎵 Multi-Class Genre Classification
Analyzed Spotify audio features to classify music genres using multiple ML algorithms. Achieved 85%+ accuracy in genre prediction and discovered key audio characteristics distinguishing genres.
🏠 Real Estate Sales Prediction
Developed an interactive web application using Texas housing data to forecast sales trends. Enabled real-time predictions for city-specific and global housing market analysis.
🌾 Crop Row Detection (Computer Vision)
Implemented U-Net architecture for semantic segmentation of crop rows from aerial imagery. Optimized model performance using IoU metrics and advanced image preprocessing techniques.
HIV Drug Prediction Model
QSAR machine learning system predicting HIV compound efficacy with 87.3% accuracy on 40K+ pharmaceutical compounds. Built complete MLOps pipeline with REST API deployment and model monitoring.
💭 Consumer Sentiment Analysis
Built sentiment classification models achieving 79.83% accuracy on customer feedback. Implemented text preprocessing, feature extraction, and created visualizations for insight discovery.
🛒 Walmart Sales Forecasting
Predicted weekly sales for 45 Walmart stores using historical data, holiday indicators, and economic factors. Implemented gradient boosting and neural networks for accurate forecasting.
Professional Experience
Data Assistant
Research Assistant
AI/ML Data Engineer
Software Engineer
Education & Certifications
Master of Science in Applied Data Science
Dean's Scholarship Recipient
Coursework: Data Analytics using Python and R, Data Visualization(Tableau, Power BI), Machine Learning-Deep Learning, Cloud Computing, DBMS, Statistics (SAS, R)