Machine Learning Engineer, Ecommerce Risk Control

What you'll do

• Build and deploy machine-learning algorithms and prototypes to address e-commerce business risks; design experiments and share findings with Product and Tech teams.
• Develop data-querying infrastructure and use analysis to identify evolving attacks, weaknesses, and opportunities in risk defenses.
• Define and monitor risk metrics, align stakeholders on goals, and communicate results through technical documents, visualizations, and presentations.

What they ask for

• Master’s degree in Computer Science, Mathematics, Machine Learning, or another relevant STEM major (finance may be relevant for financial fraud roles).
• 3+ years of hands-on experience building and delivering machine-learning models for large-scale projects.
• Programming experience in Java, C++, Python, or a related language; track record developing and implementing models and visualizations using programming or scripting languages.
• Experience with forecasting, machine-learning, and statistical tools, and communicating results, plans, or risks clearly.

Nice to have

• PhD in Computer Science, Machine Learning, Statistics, Operations Research, or a relevant field.
• 4+ years of industry experience in predictive modeling and analysis; experience with product, operations, and engineering teams or in e-commerce fraud/risk control is also noted as a plus.

Tools

Java, C++, Python, Scala, R, Ruby, Matlab

AI focus

Develop machine-learning solutions to prevent and detect e-commerce risks, including account integrity issues, incentive abuse, malicious activity, brushing, click-farm activity, and information leakage.