Decision Scientist, Fraud and Merchant Risk

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 Merchant Risk Decision Scientist team is dedicated to refining the efficiency and accuracy of our merchants' risk strategy. Sitting at the intersection of data analytics, machine learning, and automation, our team is comprised of skilled data scientists and risk analysts. Our mission is to create a secure and efficient ecosystem where merchants can thrive, transforming risk challenges into growth opportunities. As a Decision Scientist in Merchant Risk, you will play a pivotal role in leveraging advanced analytical tools and machine learning models to enhance the merchant onboarding experience, striking the perfect balance between mitigating risk and optimizing the onboarding process.

• Design and implement automation solutions to streamline risk assessment and management processes.
• Build and maintain visualization dashboards to track risk performance and guide business decisions.
• Set up monitoring alerts and tracking processes to prevent unexpected merchant losses.
• Perform exploratory and vendor analysis to evaluate potential business opportunities.
• Develop and execute resolution plans for merchant chargebacks, overdue payments, abusive disputes, and other unexpected losses.
• Collaborate with data, feature, modeling, and engineering teams from partner groups to develop innovative risk solutions.

Your contributions will be critical in reducing merchant risk while ensuring a seamless onboarding experience. By implementing effective risk strategies and automation solutions, you will help create a safer, more efficient ecosystem for our merchants, ultimately driving business growth and stability.
Technologies we use (and teach):

• Programming Languages: SQL, Python (Pandas, Numpy), R (Tidyverse)
• Data Visualization: Tableau, Looker, Plotly, ggplot
• Platform & tools: Snowflake, AWS, Salesforce, Github/Git, Airflow, GCP, DataBricks
• Machine Learning: Scikit-Learn, TensorFlow, PyTorch, Keras

Qualifications
You Have:

• Bachelor's degree in DataScience, Statistics, Mathematics, Computer Science or a related field. A Master's degree is preferred.
• 2+ years of experience in data science, data analysis, or a related field.
• Proven experience in fraud detection and risk management.
• Strong knowledge of data analysis techniques.
• Proficiency in SQL
• Proficiency in programming languages such as Python or R.
• Proficiency in at least 1 data visualization tool
• Excellent problem-solving skills and attention to detail.
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Qualifications
You Have:

• Bachelor's degree in DataScience, Statistics, Mathematics, Computer Science or a related field. A Master's degree is preferred.
• 2+ years of experience in data science, data analysis, or a related field.
• Proven experience in fraud detection and risk management.
• Strong knowledge of data analysis techniques.
• Proficiency in SQL
• Proficiency in programming languages such as Python or R.
• Proficiency in at least 1 data visualization tool
• Excellent problem-solving skills and attention to detail.
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.