Summary
Xin Ning is a data scientist with 8 years of experience blending rigorous applied-math training from Northwestern with hands-on product analytics at Apple, Uber, and Vibes. She specializes in R, SQL and scalable dashboard automation, having saved teams 100+ hours by automating reporting and built analytics templates for mobile marketing and fraud detection. At Uber she translated IMU and operational data into a scalable legal-case analysis method and designed experiments to drive safer driver behavior, and at Apple she focuses on fraud engineering and risk algorithms. Comfortable bridging technical and business stakeholders, she combines statistical rigor, A/B testing experience, and practical machine learning to turn complex datasets into actionable decisions. Notably, she pairs engineering curiosity (web development on GitHub) with a knack for communicating the story behind the numbers to diverse audiences.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Economics, Financial Engineering, Bachelor of Economics, Financial Engineering at Zhongnan University of Economics and Law
Master of Science (M.S.), Engineering Science and Applied Mathematics, Master of Science (M.S.), Engineering Science and Applied Mathematics at Northwestern University