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Machine Learning Engineer

2 months ago

San Francisco, California, United States Block Full time

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
Job Description
Machine Learning is an integral part of how we design products, operate, and pursue Cash App's mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use artificial intelligence to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day. Check out our Machine Learning / AI blog here
This role is part of Cash App's Risk ML team and will be embedded within one of the below workstreams:
Identity: Using machine learning methods and systems, this team reduces the prevalence of inauthentic identities in Cash's ecosystem, provides a first line of defense against bad actors attempting to circumvent our IDV controls while simultaneously building our confidence in existing and new customers' identities. Our goal is to ensure that every individual has access to the financial services they need, regardless of their background or financial history. We believe that ML has the potential to revolutionize the way in which identity verification is conducted, and we are dedicated to constantly improving and refining our solutions to ensure that it remains at the forefront of this rapidly evolving field. By using machine learning for identity verification, we aim to create a safer and more inclusive financial system for all.
Cash Card + Disputes: This team owns analytical and ML solutions for the full lifecycle of the Cash Card product with a focus on mitigating risk/fraud. Team works cross-functionally with Product, Platform, Legal, and others to balance financial loss to the business, regulatory risk, and the holistic customer experience.
Qualifications

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree is preferred
  • 6+ years of experience in machine learning, data analysis, or a related field
  • Strong knowledge of machine learning algorithms and data analysis techniques
  • Excellent problem-solving skills and attention to detail
  • Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders
  • Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
  • MySQL, Snowflake, GCP/AWS and Tableau

Qualifications

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree is preferred
  • 6+ years of experience in machine learning, data analysis, or a related field
  • Strong knowledge of machine learning algorithms and data analysis techniques
  • Excellent problem-solving skills and attention to detail
  • Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders
  • Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
  • MySQL, Snowflake, GCP/AWS and Tableau