About the team:

The Account Defense team puts an end to fake accounts and stops account takeover by using real-time machine learning to look at more than 16,000 signals that identify good and bad users with unparalleled accuracy. Sift provides consumer-facing companies an account defense solution that blocks bad actors, removes unnecessary friction for good actors, and allows the customer to make a quick decision on “gray” cases. Sift enables its customers to automate an ever-growing share of their detection and prevention processes, to provide real-time protection to end users and reduce the load on the customer's security, fraud/risk and operations teams. 

What you’ll do:

  • Work with rich online account defense data that spans multiple years
  • Deep dive into the account defense space, drive data-powered initiatives to improve machine learning model accuracy
  • Develop mechanisms that automatically explain how a model arrived at a prediction
  • Provide meaningful and actionable insights to customers to identify and prevent fraudulent behaviors and transactions
  • Leverage anomaly detection algorithms to identify and explain unusual patterns of customers traffic
  • Research and experiment with machine learning algorithms to adapt to fast changing fraud patterns
  • Collaborate with Product Managers, customer facing teams, data scientists, and engineers to identify customer needs and opportunities, define features, and deliver production solutions.

What would make you a strong fit:

  • Strong understanding of machine learning and data science concepts, and a track record of solving problems with these methods
  • 5+ years of experience working with large scale data sets, using Jupyter, Pandas, PySpark, PyTorch, Tensorflow or similar technologies
  • 3+ years of experience working as a data scientist at a technology-focused company
  • Proficiency in multiple machine learning or statistical packages in Python, R, MATLAB, or another programming language, and SQL
  • Strong communication & collaboration skills, impact-driven, and believe that team output is more important than individual output
  • Advanced degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, or a related field

Bonus points:

  • Experience in Java or other object-oriented programming languages
  • Experience working with large datasets using Spark, MapReduce, or similar technologies
  • Experience with large-scale end-to-end machine learning models training and inferencing

A little about us:

Sift is the leading innovator in Digital Trust & Safety.  Hundreds of disruptive, forward-thinking companies like Airbnb, Zillow, and Twitter trust Sift to deliver outstanding customer experience while preventing fraud and abuse.

The Sift engine powers Digital Trust & Safety by helping companies stop fraud before it happens. But it’s not just another anti-fraud platform: Sift enables businesses to tailor experiences to each customer according to the risk they pose. That means fraudsters experience friction, but honest users do not. By drawing on insights from our global network of customers, Sift allows businesses to scale, win, and thrive in the digital era.

Benefits and Perks:

  • Competitive total compensation package
  • 401k plan
  • Medical, dental and vision coverage
  • Wellness reimbursement
  • Education reimbursement
  • Flexible time off

Sift is an equal opportunity employer. We make better decisions as a business when we can harness diversity in our experience, data, and background. Sift is working toward building a team that represents the worldwide customers that we serve, inclusive of people from all walks of life who can bring their full selves to work every day.

This document provides transparency around the way in which Sift handles personal data of job applicants: https://sift.com/recruitment-privacy

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