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Cash App

Staff Machine Learning Engineer (Modelling), Risk

Posted 15 Days Ago
Be an Early Applicant
Hybrid
Sydney, New South Wales
Senior level
Hybrid
Sydney, New South Wales
Senior level
You will build machine learning models to detect fraud in real time, analyze fraud patterns, collaborate with engineering and product teams, and mentor other modellers, requiring a high level of autonomy and responsibility.
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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 50+ 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.
The Role
Machine Learning is an integral part of how we at Cash App design products, operate, and pursue our 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 ML and AI methods 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.
As part of the Risk ML team, you will build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal to analyse emerging fraud patterns, engineer new features for risk models, and deploy robust models to take action on bad activity in real time.
This role can work remotely from anywhere in Australia or New Zealand, or from our offices in Melbourne, Sydney and Auckland.
You Will

  • Be responsible for building machine learning models to detect and act against fraudulent activity, as well as researching emerging fraud patterns, and leading and participating in cross-functional initiatives to tackle problems.
  • Collaborate cross-functionally with our engineering, product, and operations teams located across Australia and the United States (particularly Melbourne and San Francisco) to keep our customers and their money safe.
  • Work closely with the ML Engineering teams who build the systems that allow our models to operate at scale and in real time.
  • Contribute to the growth of our modelling capabilities through mentoring and supporting fellow modellers
  • Exercise a high level of autonomy and responsibility, own your solutions from design through to operation


You Have

  • Bachelor's degree in a quantitative field such as Mathematics/Statistics/Physics or Machine Learning. Masters or PhD preferred
  • 5+ years of experience in machine learning, artificial intelligence, 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


Technologies We Use and Teach

  • Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
  • MySQL, Snowflake, Tableau, Mode
  • GCP/AWS


We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.
We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page .
Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.
Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.
Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we're helping build a financial system that is open to everyone.

Top Skills

Python

Cash App Sydney, New South Wales, AUS Office

Our Sydney office is small and mighty. Like a habanero. Sydney is famous for its golden beaches, world-class restaurants, and Cash App engineers.

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