- Published: October 17, 2021
Riskified is the AI platform powering the eCommerce revolution. We use cutting-edge technology, machine-learning algorithms, and behavioural analytics to identify legitimate customers and keep them moving toward checkout. Merchants use Riskified to increase revenue, prevent fraud, and eliminate customer friction. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for merchants across virtually all industries, including a number of Fortune 500 companies.
About the Role
The Models Training team is responsible for the data sampling, training, validation and deployment of Riskified’s fraud prevention models. The team trains models for new and existing segments and continuously seeks to improve the performance for our industry and merchant-specific models.
As a Research Analyst on the team, you’ll have ownership over all the models in your industry and have ultimate responsibility for their performance. You’ll search for new ways to segment the industry and engineer new features to train more accurate models, leveraging your expertise of the fraud trends within your industry. Finally, you’ll collaborate closely with our operation teams and act as the Data Science department’s expert for all matters regarding your domain.
What You'll Be Doing
- Build and optimize classifiers using machine learning techniques, engineer features to further enhance the models’ performance
- Work closely with the business analytics and account management teams to identify needs and provide value where most needed
- Work closely with the Data Science teams to improve the training and validation methodologies used in production
- Master the online fraud prevention domain through hands-on analysis of live data with our in-house analysis tools
- Develop compelling reports that are backed by data, comparing models performance and validations techniques
- Hands-on analytics experience for at least 2-3 years
- Bachelor's degree, preferably in a quantitative field (i.e. mathematics, statistics, computer science, natural sciences)
- Proficient in R - modelling, functions creation and data wrangling
- Ability to write clean and concise code, hands on experience with the Tidyverse package - advantage
- Proficient in SQL
- Good communication skills, ability to clearly explain complex concepts.
- High level of English, including experience in writing research reports and summaries