Ayala Waichman

Senior Data Scientist @ Trax

About Ayala Waichman

Ayala Waichman is a Senior Data Scientist at Trax Retail, specializing in anomaly detection and business-oriented modeling. With a background in economics and statistics from Ben Gurion University, she has extensive experience in data analysis across various companies in Israel.

Work at Trax

Ayala Waichman has been employed at Trax Retail as a Senior Data Scientist since 2018. In this role, she focuses on deriving customer insights through data analysis. Her work involves utilizing advanced data science tools and technologies to enhance the company's capabilities in image recognition and retail analytics. She has contributed to various projects that leverage data to inform business strategies and improve operational efficiency.

Previous Experience in Data Science

Before joining Trax, Ayala Waichman held several positions in data science and analytics. She worked at William Hill as a Decision Science Analyst from 2016 to 2018 in Tel Aviv, Israel. Prior to that, she was a Senior Data Mining Analyst at 888 Holdings for one year, from 2015 to 2016, also in Herzliya, Israel. Her career began at G-Stat, where she served as a Senior Data Mining Analyst from 2010 to 2015, contributing to projects at Discount Bank.

Education and Expertise

Ayala Waichman studied at Ben Gurion University, where she earned a Bachelor of Arts degree in Economics and Statistics from 2006 to 2010. Her academic background provides a strong foundation for her expertise in data science, particularly in anomaly detection modeling and business-oriented modeling aimed at cost reduction. This educational experience supports her current work in deriving insights from complex data sets.

Technical Skills and Tools

In her role as a Senior Data Scientist, Ayala Waichman utilizes a variety of advanced tools and technologies. She is proficient in using Pandas, Sklearn, PySpark, SQL, and BigQuery for data science projects. These tools enable her to analyze large data sets, develop predictive models, and extract actionable insights that drive business decisions.

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