Swaroop M. Email & Phone Number

Teaching LLMs how to code!

- Solved and documented complex coding challenges, ensuring the generation of accurate and comprehensive training data for large language models (LLMs) in Python, SQL, data analysis, data science, and machine learning.- Explained intricate problem-solving processes and coding methodologies, enabling LLMs to better imitate human reasoning and improve performance on sophisticated tasks.

Boston, Massachusetts, United States

Teaching Assistant for the course CS699 Data Mining

Bengaluru, Karnataka, India

• Ensured data integrity and accuracy of large datasets for analytics and reporting by implementing robust data quality checks and monitoring processes.• Conducted performance tuning and optimization of SQL queries, enhancing data warehouse efficiency and ensuring seamless data retrieval and processing.• Supported large-scale deployments of data ingestion and modeling processes onto the production server.• Enhanced data reliability and accuracy by architecting robust ETL workflows leveraging Spark for high-speed data processing.• Analyzed large data sets using Hive and handled ETL job failures daily using shell scripting and Hadoop (HDFS).• Automated repetitive tasks and daily data analysis through Unix scripting, Python, and SQL, saving 2 hours daily and increasing efficiency by 25%.• Achieved a 95% conflict resolution rate with stakeholders and streamlined onboarding by documenting critical project details.• Led finance reporting, producing key business reports monthly, including KPIs with Hive and Excel.• Collaborated with cross-functional teams to understand their requirements and provided them with clean, well-organized data sets.

Hyderabad

• Developed and exhibited a prototype Blockchain network for financial transactions using Hyperledger fabric.• Integrated a printer with Raspberry Pi to print a receipt in order to demonstrate to clients how the prototype network works on financial transactions made between 2 parties.

Vishakhapatnam Area, India

• Built and fine-tuned machine learning models, like SVM and Decision trees, and performed cluster analysis to detect anomalous energy consumption patterns in residential buildings.• Developed interactive dashboards to visualize complex energy grid data using Tableau, matplotlib, and QGIS, enabling data-driven decision-making for energy grid optimization.• Researched deep learning techniques like CNN to classify streetlamp malfunctions via image recognition using Python and TensorFlow.• Worked closely with senior engineers to fine-tune models and optimize their performance, achieving a 20% increase from the baseline.• Teamed up with diverse experts from various teams to collect, clean, and preprocess data for model training, ensuring data integrity.

Master Of Science - Ms, Applied Data Analytics, 3.93

Courses 1. Foundations of Machine learning 2. Foundations of Data Analytics and Visualization 3. Data Mining 4. Data Science with Python.

Bachelor Of Technology, Computer Science, 8.68