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Principal Applied Scientist at Zillow | Kaggle Grandmaster
My professional experiences has centered on advanced analytics and applied machine learning. In analytics I enjoy the process of bringing ideas to life. Most of what I do falls into three categories: Data Exploration: about 30% of what I do is gathering, re-shaping and exploring complex, dirty, large-scale data. Usually SQL, Hive, Spark to munge terabytes of data down to something I can analyze in Python, R or SAS. Machine Learning: most of my time today is spent on building machine learning solutions. From helping customers frame a problem to delivering production ready solutions, I touch all aspects of building impactful models. My favorite parts are feature engineering and thoughtful cross validation. Building Data Products: I use quantitative approaches to build and prototype solutions that add business value. My philosophy in analytics boils down to achieving the right mix of three key elements I believe each and every piece of analytics should be made of: analytical rigor (the "science"), creativity (the "art"), practicality (customer focus). I have enjoyed participating in Machine Learning competitions on Kaggle where I have earned Kaggle's highest status of GrandMaster (only 76 in the world). To date I've won two competition and I've been ranked as high as 12th out of 600,000 data scientists from all over the world. Kaggle is not only fun but provides a great platform to get exposure to applied machine learning in various industries. To date I've tackled problems ranging from retail sales forecasting to social media natural language processing, from loan default prediction to identification of fraudulent activities on e-commerce websites. My winning model in the Avito competition (described below in my profile) is used to identify illegal content in more than 22 millions ads each day on the third largest classifieds website in the world. Geeky stuff asi
Alma Mater Studiorum – Università di Bologna
Master of Science (M.S.), Biostatistics
January 1, 2003 – January 1, 2004
Sapienza Università di Roma
Master of Science (MS), Statistics
January 1, 1994 – January 1, 1999
Zillow
Principal Applied Scientist
July 1, 2023 – Present
Seattle, Washington, United States
Zillow
Senior Applied Scientist
July 1, 2021 – July 1, 2023
Seattle, Washington, United States
Premera Blue Cross
Principal Data Scientist (Machine Learning & Deep Learning)
April 1, 2016 – June 1, 2021
Premera Blue Cross
Senior Data Scientist
January 1, 2013 – March 1, 2016
Premera Blue Cross
Senior Statistician
October 1, 2010 – December 1, 2012
Premera Blue Cross
Statistician
August 1, 2004 – September 1, 2010
Ministero della Salute
Statistician
July 1, 2000 – February 1, 2004
Rome Area, Italy
Cloudera Certified Professional: Data Scientist
Cloudera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long tenure at Premera Blue Cross (17 years) and Zillow (3 years and current), indicating loyalty and stability. Their experience spans healthcare and real estate, demonstrating adaptability across different industries. The progression through various data-focused roles (Statistician, Data Scientist, Applied Scientist) shows a continuous learning mindset and a drive for growth. The focus on AI, machine learning, and deep learning aligns with modern data-driven cultures. However, the lack of diverse company experience outside of these two long tenures might suggest a preference for established environments.
Soft Skills & Operational Fit
The candidate's career progression from Statistician to Principal Applied Scientist at major companies like Zillow and Premera Blue Cross suggests strong analytical, problem-solving, and leadership skills. Their work on user engagement and personalized recommendations indicates a customer-centric approach. The description of identifying business opportunities and helping leadership make data-driven decisions points to good communication and strategic thinking. However, without specific project details or interview data, it's difficult to assess collaboration or stress handling directly.