Varshini Yaganti

About Varshini Yaganti

I’m a Data Analyst with 3.5+ years of experience working at the intersection of analytics, machine learning, and cloud data platforms. I enjoy turning messy, complex data into insights that actually help teams make better decisions. My background spans consulting, fintech, and academia, where I’ve worked on everything from predictive models to executive dashboards.At KPMG, I focus on building AI-powered analytics solutions that support risk forecasting, fraud detection, and large-scale financial analysis. I’ve designed end-to-end machine learning pipelines, created interactive dashboards for leadership, and worked extensively with cloud platforms to ensure data is reliable, automated, and well-governed. A big part of my role is making sure insights are not just accurate, but also easy for stakeholders to understand and act on.My core skill set includes:Analytics & Programming: Python, SQL, R, exploratory data analysis, statistics, A/B testing, and time series analysisMachine Learning & AI: Scikit-learn, TensorFlow, PyTorch, feature engineering, predictive modeling, NLP, model explainability (SHAP, LIME), and GenAI with prompt engineeringBI & Visualization: Power BI, Tableau, DAX, dashboard design, and data storytellingData Engineering & Cloud: ETL/ELT pipelines, Azure ML, Azure Synapse, Snowflake, AWS Glue, Redshift, BigQuery, and PySparkDev & MLOps: Git, MLflow, CI/CD basics, workflow automation, and reproducible experimentsAlongside industry work, I’ve also been a Graduate Teaching Assistant and Research Assistant, where I mentored students in data science and machine learning, led hands-on labs, and contributed to research on model interpretability and bias detection. Teaching has helped me become a better communicator—especially when explaining complex technical ideas to non-technical audiences.I’m driven by curiosity, continuous learning, and collaboration. I’m especially interested in AI/ML analytics, cloud BI, fraud and risk analytics, data engineering, and GenAI, and I enjoy working with teams that value thoughtful, data-driven problem solving.

Experience

1. Data Analyst

   KPMG

   Aug 2025 — Present · Marietta, GA, US

   Spearheaded development of AI-powered financial analytics dashboards using Python, SQL, and Power BI, enabling executives to forecast key risk metrics across $450M in client portfolios, demonstrating strong strategic insight.• Engineered end-to-end machine learning pipelines with scikit-learn, TensorFlow, and Azure ML, improving prediction accuracy of audit anomalies by data points monthly and reducing manual validation time by 68 hours per audit cycle. • Orchestrated cloud migration of structured and unstructured data to Azure Synapse and Snowflake, consolidating 1.2 TB of financial data into centralized models, enhancing data reliability and accelerating reporting delivery by 3 business days. • Collaborated with KPMG’s Advisory and Risk Analytics teams to deploy AI-driven fraud detection models, identifying 340+ high-risk transactions across banking clients, strengthening data governance and compliance under SOX frameworks. • Directed creation of marketing intelligence dashboards leveraging NLP, ChatGPT API, and Tableau, uncovering market sentiment trends across 12 industries, driving insights used in KPMG’s Digital Trust & Transformation practice. • Pioneered a cross-functional AI enablement initiative, mentoring 4 analysts on prompt engineering, MLOps, and data storytelling, resulting in a 2x increase in internal project adoption rate and positioning KPMG as a leader in AI-powered consulting.

Education

• Vignan Nirula Institute of Technology and Science for women

  Bachelor of Technology - BTech, Information Technology

• Kennesaw State University

  Master's degree, Computer Science