ISyE Seminar “Finding the perfect salesperson: Advanced job matching models in Bravado”
Please join us for our next seminar of fall semester in person! This seminar will feature Yoni Acriche from Bravado who will discuss advanced job matching models.
3:30 p.m. - Graduate seminar
Walter Library, Room 402
4:30 p.m. - Reception, coffee and cookies
Walter Library, Room 401
Yoni Acriche
Co-Founder and Chief Data Scientist
Bravado, Austin
About the seminar
The performance of the sales team directly affects companies’ revenue, and the alternative cost of a bad hire is often much greater than the hire’s annual salary. However, only 43 percent of sales hires hit their revenue targets in 2021, and the average tenure of a salesperson decreased to less than 12 months. Given this, it’s no surprise that sales is considered one of the most challenging roles to hire. Bravado, a Series B startup, aims to ease the process and minimize the risks associated with hiring sales employees. By building the world’s largest professional network for salespeople, Bravado uses a novel data-driven approach to make hiring easier, increase transparency, and help candidates and companies find better fits. In this presentation, co-founder Yoni Acriche will cover the data architecture of Bravado’s sales hiring matching solution, discuss the strategy of picking the right Machine Learning approach, and explain in detail the neural network model that powers the matching algorithm and its empirical results.
Papers:
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
- Product Titles-to-Attributes As a Text-to-Text Task
About the speaker
Yoni Acriche is the Co-Founder and Chief Data Scientist of Bravado, a Series B startup funded by Tiger Global, Redpoint, and Freestyle VC. Acriche focuses on leveraging machine learning to make the community members more successful and increase the company’s operational efficiency. Prior to Bravado, Yoni was the Head of Data Science at Salespredict (acquired by eBay), and the Head of Seller Experience Research at eBay.
His research focuses on using large-scale neural network language models to increase the efficiency of online marketplaces. His work was published in top machine learning conferences such as the Association for Computing Linguistics (ACL), Web Search and Data Mining (WSDM), and the Association for Computing Machinery (ACM), as well as in the Harvard Business Review.