Machine Learning Engineer, Commerce Fraud Risk (Modeling)

Company Description

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible.

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

Check out our locations, benefits, and more at cash.app/careers.

Job Description

The Fraud Risk Team supports the commerce fraud risk strategy and merchant risk teams with models and risk indicators to manage the risk key metrics. We collaborate with multiple engineering teams to create the capacity of serving next generation AI solutions.  

As a Machine Learning Modeler on the Fraud Risk Team, you will be responsible for developing and implementing machine learning models to detect and prevent fraudulent activities. This role requires a strong understanding of machine learning algorithms, data analysis, and fraud detection techniques.

You will:

• Develop, implement, and maintain machine learning models for fraud detection.
• Analyze large datasets to identify patterns and trends related to fraudulent activities.
• Collaborate with cross-functional teams to understand business needs and develop solutions to mitigate fraud risks.
• Continuously monitor and evaluate the performance of machine learning models, making adjustments as necessary.
• Stay up-to-date with the latest developments in machine learning and fraud detection, and incorporate new techniques and technologies into our processes as appropriate.
• Prepare and present reports on model performance and fraud trends to stakeholders.

Qualifications

You have:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree is preferred.
• 5+ years of experience in machine learning, data analysis, or a related field.
• Proven experience in fraud detection and risk management.
• Strong knowledge of machine learning algorithms and data analysis techniques.
• Proficiency in programming languages such as Python or Java.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Technologies we use and teach:

• Python (NumPy, Pandas, sklearn, TensorFlow, PyTorch, keras, etc.)
• Snowflake, DataBricks, GCP, AWS
• Classical classification / regression models. Deep Learning including Sequential modeling, Graph modeling and Transformer based models

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $167,300 - USD $204,500
Zone B: USD $158,900 - USD $194,300
Zone C: USD $150,600 - USD $184,000
Zone D: USD $142,200 - USD $173,800

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Full-time employee benefits include the following:

• Healthcare coverage (Medical, Vision and Dental insurance)
• Health Savings Account and Flexible Spending Account
• Retirement Plans including company match 
• Employee Stock Purchase Program
• Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance 
• Paid parental and caregiving leave
• Paid time off (including 12 paid holidays)
• Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees) 
• Learning and Development resources
• Paid Life insurance, AD&D, and disability benefits