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F5

Data Scientist

United States, Texas
Details

Responsibilities:

  • Work closely with customers to quickly understand their fraud challenges, and identify how F5 might be able to help them successfully fight fraud.

  • Identify useful data from customers’ web and mobile applications, and engineer relevant features for fraud models.

  • Train and deploy machine learning models to predict fraud outcomes, based on telemetry and customer-provided data.

  • Maintain models for customers, and update or refresh them as needed.

  • Communicate clearly and effectively with internal teams (sales, customer success, product, engineering, etc) and with customers on the performance of machine learning models, as well as other fraud and data science issues.

  • Provide feedback to internal teams on data science, product, engineering issues, and suggest process improvements.

Requirements:

The ideal candidate would have:

  • Strong analytical skills including the ability to manipulate, model, interpret and visualize large quantities of structured data.

  • Strong proficiency in Python and SQL

  • Experience with building and deploying machine learning models on large-scale data. Experience working with highly unbalanced data (e.g. commonly found in fraud use cases) a strong plus.

  • A passion for delighting customers, and an aptitude for engaging with customers on fraud, security and machine learning issues on a regular basis. Prior experience working with customers on complex fraud or security issues would be a strong plus.

  • Familiarity with common web and mobile technologies.

  • Strong interpersonal skills, personable, and persistent. A good listener. Self-motivated, able to work well both independently and as part of an agile team.

  • A demonstrated enthusiasm and capacity to learn new technologies quickly.

  • A scrappy yet meticulous approach, and a love for problem solving!

The Job Description is intended to be a general representation of the responsibilities and requirements of the job. However, the description may not be all-inclusive, and responsibilities and requirements are subject to change.