Sai Vamshi Challamalla

About Sai Vamshi Challamalla

I bring 4 years of experience building and deploying data science and AI solutions that turn complex, real-world problems into measurable business outcomes. With a strong foundation in statistics and machine learning, I’ve worked across fintech, public-sector finance, insurance, and private equity often taking ideas from messy data to production-ready systems.From forecasting demand and detecting anomalies in large transactional systems to building risk models for financial decision-making, I’ve consistently blended business context with ML. More recently, I’ve designed and deployed Generative AI systems LLM-powered analytics, RAG pipelines, and agentic workflows—to automate research, due diligence, and document-heavy workflows with high accuracy and traceability.Tech Stack Highlights: Python, SQL, PySpark, Power BI, Scikit-learn, PyTorch, TensorFlow, AWS (EC2, S3, Bedrock, SageMaker), LangChain, FAISS, Docker, Kubernetes, REST APIsI hold a Master’s in Data Science from CU Boulder (4.0 GPA). I enjoy fast-paced, cross-functional environments, working on ambiguous problems, and building AI systems that are scalable, explainable, and actually used by stakeholders.Let’s connect if you’re working at the intersection of Data Science, ML, and GenAI or if you’re looking for someone who can turn complexity into clear, deployable solutions.

Experience

1. Data Scientist

   Quantum Performance Partners

   Jul 2025 — Present · Denver, CO, US

   Analyzed large-scale financial statements, deal data, and market benchmarks to support private-equity due diligence, valuation, and investment decisions.Built machine learning and analytics pipelines (XGBoost, Random Forests, regression, time series) to evaluate revenue growth, EBITDA margins, leverage ratios, and downside risk across M&A deals.Applied statistical validation techniques including hypothesis testing, trend analysis, and error analysis to ensure models aligned with real-world financial behavior.Designed interactive Power BI dashboards combining KPIs, forecasts, and risk indicators used by partners for faster deal comparison and capital allocation.Built and deployed a production AI analytics application on AWS (EC2, S3, Bedrock) using Docker, integrating LLMs with RAG pipelines (LangChain, FAISS) to automate investment memos and deal summaries.Developed REST-based AI services with logging, retries, and monitoring to support reliable, scalable inference in production.Partnered closely with investment professionals, product managers, and engineers to turn ambiguous business questions into deployable AI solutions.

Education

• University of Colorado Boulder

  Master of Science - MS, Data Science

• CVR College of Engineering, Hyderabad

  Bachelor of Technology - BTech, Computer Science