Senior Data Scientist - Machine Learning

San Francisco

Sift logo
Sift
Apply now Apply later

Posted 4 weeks ago

About the team:

At Sift we enhance trust and safety in the digital world with our AI driven technology platform. Our products deliver payment protection, ensure content integrity, and protect account abuse and takeover for businesses around the world. We believe that machine learning is the way to empower internet-scale businesses to prevent fraud and improve trust.

We are a group of machine learning focused software engineers and data scientists working on products to enhance trust and safety of the internet. By providing a clear, accurate assessment of risk at multiple points of the end-user journey, we enable businesses to eliminate losses from fraud, and create adaptive, frictionless experiences for end-users. You will have the opportunity to collaborate with strong engineers, product managers and designers to build highly available and real-time systems to detect and prevent fraud for our customers.

What you’ll do:

  • Work with rich online payments data that spans multiple years
  • Deep dive into the payments protection space, drive data-powered initiatives to improve machine learning model accuracy
  • 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
  • Develop mechanisms that automatically explain how a model arrived at a prediction
  • Research and experiment with machine learning algorithms to adapt to fast changing fraud patterns
  • Collaborate with Product Managers, client facing teams, and engineers to identify customer needs and opportunities, define features, and deliver production solutions.

What would make you a strong fit:

  • 3+ years of experience working with large scale data sets
  • Strong understanding of machine learning and data science concepts, and a track record of solving problems with these methods
  • 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 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 thought, 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, so we can Win as One Team.

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

Job tags: AI Engineering Machine Learning Matlab Python R Research Spark SQL