Available to hire
Hi, I’m Sai Venkat Choppara, a software engineer with a passion for building scalable backend systems, data pipelines, and AI/ML solutions in finance and IT. I enjoy turning complex data into actionable insights and delivering automation that accelerates decision-making. My interests focus on CLV modeling, predictive analytics, and Generative AI with RAG architectures to enhance risk assessment and portfolio optimization.
Outside of work, I’m always exploring new data tools, refining cloud-based data platforms, and collaborating with cross-functional teams to deliver measurable impact through analytics and engineering excellence.
Skills
Language
Afar
Advanced
Work Experience
Software Engineer at Citigroup
May 1, 2025 - PresentEngineered and integrated multi-source financial datasets including trade transactions, market data, and client portfolio data into AWS Redshift, improving query performance and reducing analytical runtime by 10%. Performed data cleansing and transformation using Python (Pandas) and SQL, resolving missing values, data inconsistencies, and classification errors, improving data quality by 35% and increasing reporting accuracy by 12% across financial analytics workflows. Built and deployed machine learning models (Random Forest, SVM) using Scikit-learn and TensorFlow to predict market risk exposure, credit risk, and portfolio volatility, enabling proactive risk mitigation strategies. Applied NLP techniques using Hugging Face Transformers (BERT) to analyze unstructured financial data (earnings reports, analyst notes, client communications), enabling sentiment analysis and risk profiling. Created interactive Tableau dashboards to monitor key financial metrics including P&L, Value at Risk (V
Software Engineer at Infosys
April 1, 2022 - July 1, 2024Developed and maintained Power BI dashboards to monitor application performance, system health, infrastructure utilization, and operational KPIs, improving visibility and decision-making for support and engineering teams. Built ARIMA and Linear Regression forecasting models using Python (Pandas, NumPy, Scikit-learn) to predict system load, capacity requirements, and incident trends, achieving 85% forecasting accuracy. Automated data cleansing, validation, and transformation workflows using Talend ETL, improving data quality, consistency, and reliability by 45%. Implemented OLAP-based analytical solutions to perform multidimensional analysis of application performance, incident metrics, and infrastructure utilization across multiple environments. Designed and optimized SQL queries, stored procedures, and database objects to support large-scale reporting and analytics, improving query performance and data processing efficiency. Conducted A/B testing and statistical analysis on system con
Education
Master of Science in Information Technology at University of North Carolina at Charlotte
January 11, 2030 - June 30, 2026Bachelor of Science in Information Technology at Seshadri Rao Gudlavalleru Engineering College
January 11, 2030 - June 30, 2026Qualifications
Industry Experience
Financial Services, Software & Internet
Skills
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