Square is looking for a Data Scientist to join their Risk Machine Learning team to build processes to root out high-risk activity across the Square platform of products, identify and prevent fraud and credit risks, and promote risk effectiveness throughout Square.
Requirements
- Hands-on work building/implementing machine learning models
- Experience driving data-driven solutions and executing their implementation
- Worked on ambiguous problems and unstructured questions
- Proficiency with SQL, Python and Looker
- Familiarity with fraud/risk management, trust and safety, payments, or card business
- SQL, Snowflake, Databricks etc.
- Python (Pandas, Numpy)
Responsibilities
- Diagnose problems and develop compelling, data-driven recommendations
- Provide thought leadership in building and executing risk management strategies for new or existing product launches
- Design and analyze A/B experiments to measure the effectiveness of a Risk Management strategy
- Partner with Product, Engineering, Machine Learning Engineering, Policy and Operation teams to design solutions to business problems, influence product roadmaps, and develop new products/processes
- Use machine learning tools to develop data-driven solutions.
- Promote creative risk solutions through third-party evaluation and integration with a focus on improving the seller experience
- Effectively present your work with senior leaders and cross-functional stakeholders on a regular basis
Other
- Data scientists at Block operate very cross functionally and you’ll plug into folks from product, engineering, operations, machine learning, policy and sales to influence Square's global Risk road map and processes.
- You will also make a direct impact on Square's priorities and banking initiatives (debit card and credit card businesses, loans, etc.) by building risk detection strategies, developing/tracking key success metrics, influencing partners through data and enabling growth of the business.
- A passion for Block's mission
