Jinjin Zhang
About
Jinjin Zhang is from New York City Metropolitan Area. Jinjin works in the following industries: "Internet", "Higher Education", "Retail", and "Hospital & Health Care". Jinjin is currently Senior Data Scientist at Twitter, located in New York City Metropolitan Area. Jinjin also works as Co-Founder at Xier Health, a job Jinjin has held since Apr 2017. In Jinjin's previous role as a Lead Data Scientist at FARFETCH, Jinjin worked in New York City Metropolitan Area until Aug 2021. Prior to joining FARFETCH, Jinjin was a Lead Data Scientist at Macy's and held the position of Lead Data Scientist at Greater New York City Area. Prior to that, Jinjin was a Technical Advisor at Insight Data Science, based in Greater New York City Area from Jan 2020 to Jan 2020. Jinjin started working as Research Scientist at University of Minnesota-Twin Cities in Center for Magnetic Resonance Research in Sep 2015. From Jun 2014 to Sep 2015, Jinjin was Postdoctoral Associate at University of Minnesota-Twin Cities, based in Center for Magnetic Resonance Research.
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Jinjin Zhang's current jobs
Revenue Science
Responsible for Product & Algorithm development & Operation; Grew the startup from scratch to 60+ employees in 16 months • Created and implemented a complete set of Standard Operating Procedures for the core business process, which enabled the delivery of our unique data-driven personalized healthcare services • Developed an end-to-end image segmentation pipeline for one key product line • Led a lean engineering team to deliver the MVP of the information system, including EMR/ERP system, consumer-facing website, mobile application, and hardware data transmission solution • Recruited and trained 20+ medical and technical professionals
Jinjin Zhang's past jobs
As TLM, led a team of data scientists/MLE to develop data-driven products for private client sector: • ML & DL model pipelines for client segmentation, product recommendation and behavior prediction • Sequential Bayesian A/B testing framework for Private Client group specifically
• Developed and delivered end-to-end machine learning models/pipelines in a cross-functional team environment • Demand forecasting and pricing optimization for all lines of products across Macys.com and Macys stores
Mentored PhD level data science fellows, coaching them on project scoping, modeling strategies, product thinking, data/pipeline engineering and communication/presentations skills.
• Developed an image reconstruction pipeline in MATLAB & C++ including gridding and density correction algorithm for a mapping sequence, the application of which in nano-warming was published as the cover article on the top-tier journal "Science - Translational Medicine" • Built an imaging simulator based on spatial encoding model and PDE solver in MATLAB and C++ for the development of a portable MRI scanner Please find my publication list at my Google scholar profile: https://scholar.google.com/citations?user=KyTTz6oAAAAJ&hl=en&oi=ao
• Created four novel MRI sequences to image previously MRI-invisible components in the human body, created algorithms for signal processing & image reconstruction, and performed statistical analysis on data from their clinical applications • Developed image reconstruction pipelines in MATLAB & C++ involving gridding algorithm, kernel design, and sampling density correction