Machine Learning Model

Company Description

The story begins with an idea at Block in 2013. Originally built to ease peer-to-peer payments, Cash App has evolved from a straightforward product with a singular function to a dynamic ecosystem, crafting unique financial products, including Afterpay/Clearpay, to offer a superior way to send, spend, invest, borrow, and save to our 47 million monthly active users. Our mission is to redefine the world's interaction with money, making it more understandable, instantly available, and universally accessible.

Cash App today is represented by thousands of employees globaly working across office and remote locations. We aim to foster a culture that encourages innovation, collaboration, and impatcfulness. We've been a distributed team since the inception, and majority of our roles can be performed remotely from the countries where Cash App is operational. Regardless of the location, we customize our approach to ensure our employees can be creative, productive, and content.

Get more details on our locations, benefits, and much more at

Job Description

Position Overview:

We are looking for a Machine Learning Modeler to be a part of our Fraud Risk Modeling team. The role involves developing and implementing machine learning models to identify and prevent fraudulent practices. It requires a thorough understanding of machine learning algorithms, data analysis, and fraud detection methodologies.

Key Responsibilities:

1. Design, implement, and maintain machine learning models for fraud detection.

2. Analyzing substantial datasets to detect patterns and trends associated with fraudulent activities.

3. Work with cross-functional teams to comprehend business requirements and develop solutions for managing fraud risks.

4. Continuously evaluate and adjust the performance of machine learning models as per need.

5. Be updated with latest trends and advancements in machine learning and fraud detection, and incorporate new techniques and technologies into our processes when suitable.

6. Compile and present reports providing insights on model performance and patterns of fraud to stakeholders.

Qualifications

1. Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field is required. A Master's degree is preferred.

2. At least 6 years of experience in machine learning, data analysis, or a similar domain.

3. Demonstrated experience in fraud detection and risk management.

4. Sound knowledge of machine learning algorithms and data analysis methodologies.

5. Proficient in programming languages such as Python or Java.

6. Excellent problem-solving skills with a keen eye for detail.

7. Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Additional Information