Jun 2024 – Feb 2025 · 8 mos · New York City Metropolitan Area

• Client - PNC Bank
• Responsible for data sourcing and curation for an upcoming Machine Learning project in Anti-Money Laundering and Fraud Detection, ensuring high-quality data through cross-functional stakeholder collaboration.
• Developed Python automation scripts that accelerated the data curation process, cutting manual efforts by 50%.
• Written efficient and optimised SQL queries to extract data required for business needs to help in decision making.

Aug 2023 – May 2024 · 9 mos · United States

• [Fall '23, Spring '24]
• Led the development and deployment of Natural Language Processing (NLP) classification models, including BERT and RandomForest, using Python. Successfully implemented machine learning algorithms to identify political content on social media platforms with a high accuracy rate of 91%, demonstrating model validation and performance tuning.
• Optimized the data management and data extraction process by designing and implementing ETL scripts and SQL queries for handling over 600,000 rows of data from various Facebook pages and groups. Utilized data cleansing, data integration, and data processing techniques such as n-gram analysis and keyword-based filtering to enhance data quality and data accuracy.
• Instructed students in statistics, R programming, Microsoft Excel, data analysis, forecasting, data visualization, A/B testing, and hypothesis testing.
• Providing dedicated office hours to address any doubts or questions, ensuring a comprehensive understanding of the material.

Jun 2023 – Aug 2023 · 2 mos · United States

• In collaboration with nVerses Capital :
• Tested the performance and reliability of the file storage system by simulating server failures and conducting load testing with Python scripts. Analyzed 3+ key performance indicators, including throughput, bandwidth, and latency.
• Developed and deployed Ansible playbooks to set up required server cluster configurations in the Ceph File System, making the update process more efficient by 80% and less reliant on manual intervention.
• Designed and deployed a data pipeline using Python and a MySQL connector driver to store performance metrics in an SQL database, streamlining the data entry process and reducing manual workload by 70%.
• Leveraged Matplotlib and BI tools for data visualization to analyze performance metrics into actionable insights, driving informed decision-making.

Jan 2021 – Jun 2022 · 1 yr 5 mos

• Client - Citibank
• Developed an AI Python tool to automate financial report generation by fine-tuning an LLM natural language model, resulting in a 35% reduction in manual efforts and improved efficiency in generating data-driven narratives from data.
• Engineered a prototype that extracted and consolidated news data from 5+ API, and applied sentiment analysis techniques to gauge ESG sentiment for companies, empowering stakeholders to make informed investment decisions.
• Improved issue resolution efficiency for a banking client by 25% through data analysis with Python libraries (Pandas, Numpy, Matplotlib) and Tableau, streamlining processes and enhancing service quality.
• Integrated AWS S3 with PySpark, enabling efficient data pipeline enhancement and SQL-driven extraction of valuable insights.

Jan 2018 – May 2020 · 2 yrs 4 mos

• Implemented Sales and Marketing processes to ensure a supply of global talent for Corporate/Non-Profit organizations across Hyderabad, India.
• Coordinated with exchange participants from around the world and conducted interviews for internship positions.