Principal Data Scientist, Adversarial ML

at Intuit
Published December 3, 2022
Location Petah Tikva, Israel
Category Data Science  
Job Type Full-time  

Description

Company Overview

Intuit is a global technology platform that helps consumers and small businesses overcome their most important financial challenges. Serving more than 100 million customers worldwide, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

Come do the best work of your life! Intuit is looking for an innovative and hands-on Data Scientist to join a brand new cross-site project focused on Adversarial ML. The project is multidisciplinary (engineering, security research and data science) and is research and exploration oriented, however with the end goal of transforming the learnings into applications which will have company-wide internal impact as well as external publications and open-source libraries.

We are looking for team members that love new challenges, cracking tough problems, and working cross-functionally.

We encourage you to apply if you…

  • Are extremely passionate about exploring the field of Adversarial ML for large scale applications across use cases
  • Have built dozens of ML models and have an urge to do something very different
  • Thrive on ambiguity and will enjoy frequent pivoting that is part of the exploration
  • Are comfortable partnering with those directly involved with the different aspects of security, data science, data engineering and software development, across several groups and domains
  • Would love to be part of a brand new project

#LI-Hybrid

Qualifications

  • 7+ years’ Data Science experience, preferably with Fraud, Security or Credit Risk Detection solutions
  • MSc or PhD in a relevant field (Computer Science, Statistics, Applied Math, Econometrics, Operations Research), or equivalent research experience from the industry
  • Expertise in Data Mining algorithms and Statistical Modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, genetic algorithms, anomaly detection, recommender systems, sequential pattern discovery, or text mining
  • Well versed in Data Science languages, tools, and frameworks, including data processing platforms and distributed computing systems (for example Python, R, SQL, SkLearn, Numpy, Pandas, TensorFlow, Keras)
  • Experience in working on one of the cloud platforms: AWS, GCP, Azure
  • Prior knowledge of the Adversarial ML field - an advantage

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