Kriti Sayal

About Kriti Sayal

As a Senior Data Scientist at Wells Fargo, I apply my data science, machine learning, and natural language processing skills to solve complex business problems and deliver value to the organization. I have ~7 years of prior experience in analytics and modeling, working with leading companies like BlackRock and Cognizant.I have a Master\'s degree in Business Analytics and Information Management from Purdue University, where I learned how to leverage data and technology to drive innovation and growth. I also have a Master\'s degree in Economics from Jawaharlal Nehru University, where I developed a strong foundation in quantitative and analytical methods.My professional experience includes developing and deploying portfolio risk algorithms, detecting portfolio anomalies, predicting credit risk and outflows, reducing concentration risk, and building a NLP solutions. I have saved millions of dollars in bad loans, cut down deal turnaround time, and achieved high prediction accuracy in various projects. I have also earned multiple certifications in machine learning and financial markets.I am passionate about finding novel and impactful solutions for challenging and meaningful problems, and I enjoy collaborating with diverse and talented teams. My goal is to continuously learn and improve my skills and knowledge, and to contribute to the advancement of data science and its applications.

Experience

1. Senior Data Scientist

   Wells Fargo

   Jun 2022 — Present · San Francisco, CA, US

   Led a team of 8 to design and deploy supervised ML models for forecasting intraday and long-term ACH and wire transaction volumes, informing treasury and real time operations.• Built scalable MLOps pipelines to accelerate model deployment, ensure reliability, and enable continuous monitoring.• Developed real-time fraud detection using ensemble ML (XGBoost, Random Forest, Isolation Forest), anomaly detection, and network analysis, improving fraud capture by 35% and reducing false positives by 20%.• Designed a machine learning model in Python to assess risk levels of defaulted customers, segment them for targeted outreach, and improve pay-off rates by 12% as validated through A/B testing in collaboration with marketing teams.

Education

• Purdue University

  Master's degree, Business Analytics and Information Management

• Jawaharlal Nehru University

  Master’s Degree, Economics

  2014 — 2016

• Delhi University

  Bachelor of Arts (B.A.), Economics

  2011 — 2014