Daniel Austin

About Daniel Austin

I have 12+ years of experience working in Data Science - 7 years doing medical data science in academia and 5+ years in industry. I am currently at Grand Rounds. I have published 42+ peer-reviewed papers in journals and at conferences; several as first author and a few in industry. They can be found here: & hl=en. I recently started at Grand Rounds.I previously worked at Nike in Search Science inside the Personalization group. I worked on product ranking, language modeling, and other problems that improve the search experience for our users.Prior to this I worked at AppNexus and then Freestar improving publisher products and services by developing and supporting deployment of machine learning models on a platform that transacts billions of auctions for advertising space each day. I also designed a deep learning system to identify whether there is sensitive content in creatives (ad images). Longer ago, I was an Assistant Professor of Neurology at the Oregon Health & Science University (OHSU). My research focus was on probabilistic and statistical models relating data collected from unobtrusive behavioral monitoring systems to adverse health outcomes. In particular, I focused on identifying and modeling behavioral characteristics that precede or coincide with cognitive and physical decline – and other adverse health outcomes - in older adults. I also was actively working on techniques for behavioral and health forecasting from large, sparse data sets such as those produced by continuous in home monitoring of older adults via unobtrusive sensor networks. Most of my research is demonstrated in my publications, which can be found at the link above.Competencies: data science, machine learning, deep learning, predictive analytics, statistical (A/B) testing and causal inference, algorithm development, Spark, Python(including PySpark, Keras, TensorFlow, NumPy, Pandas, SciPy, etc.).

Experience

1. Principal Data Scientist, Commerce

   Nike

   Feb 2024 — Present · Portland, OR, US

   I build machine learning systems to power search, browse, and recommendation carousels across Nike’s digital channels, and to power some of our emails and b2b (wholesale) channels. I am responsible for the technical roadmap and all aspects of these systems (e.g, candidate generation/retrieval, ranking, sort optimization, etc.).

Education

• Oregon Health and Science University School of Medicine

  Ph.D., Biomedical Engineering

  2009 — 2013

• Oregon Institute of Technology

  Bachelor of Science (BS), Electrical and Electronics Engineering

  2004 — 2006

• University of Southern California

  MSEE, Statistical and Digital Signal Processing

  2006 — 2008

Skills

• Data Analysis
• Matlab
• Signal Processing
• Python
• Pattern Recognition
• Latex
• Programming
• Spark
• Statistics
• Simulations
• Science
• Biomedical Engineering
• Semiconductors
• Statistical Modeling
• Testing
• Analysis
• Machine Learning
• Research
• Big Data