Data Scientist, Model Risk Management

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.Team The Model Risk Management team ensures our machine learning models are safe, reliable, and compliant with regulatory requirements. We focus on building automated validation tools while maintaining high standards for model assessment. Our work helps prevent errors and bias while making sure models are used appropriately across Block. We work closely with teams throughout the company to establish practical governance frameworks, assess model performance, and share best practices. As a core part of the compliance organization, we support all key areas of Block regardless of product or market.The Role We're looking for a Data Scientist to help us make our model validation process both more efficient and more thorough. You'll split your time between hands-on model validation work and developing tools to automate these processes. Your experience validating ML models will be key in building practical solutions that help our team work more effectively.To start, you'll validate machine learning models across our anti-money laundering (AML), Know Your Customer (KYC), and sanctions screening systems. This hands-on work will help you spot patterns and opportunities where automation can help, leading to a greater focus on building and improving our validation frameworks.We're looking for someone with strong technical skills in both quantitative analysis and software engineering. You should be detail-oriented and familiar with relevant regulations and industry standards. Clear communication and the ability to work both independently and as part of a team are essential.You Will Primary Focus : Build tools that make model validation faster and more consistentCreate validation components we can reuse across different projectsDevelop automated approaches for common tasks like : Checking model performanceRunning statistical testsVerifying data qualityTesting model assumptionsTracking performance changes over timeBuild testing frameworks that work for different types of modelsCreate tools that help generate clear validation reportsSet up systems to continuously monitor model performanceImmediate Responsibilities : Assess machine learning models using statistical analysis and testingLook for patterns in validation work that could be automatedSet up ways to track how models perform over timeKeep validation documentation clear and up-to-dateWork with other teams to understand their validation needsBuild good working relationships while keeping business goals in mindYou Have Required : Advanced degree in Statistics, Mathematics, Physics, Computer Science, or related quantitative field5 years experience in model validation or risk management, with focus on machine learning models; or 3 years and a graduate degreeStrong software engineering practices and experience building maintainable, well-documented codeExpertise in Python for building robust validation frameworks and automation toolsStrong understanding of machine learning algorithms and statistical testing methodologiesAdvanced SQL skills for data analysis and validation automationExperience with test automation and software testing frameworksStrong quantitative skills with the ability to identify patterns in validation processesExperience building modular, reusable code and toolsHigh ethical standards with a commitment to integrity and professionalismPreferred : Experience developing internal tools or validation frameworksKnowledge of software development best practices (version control, unit testing, CI / CD)Experience validating models in regulatory environments (SR 11-7)Experience with AML, KYC, fraud detection, or other financial compliance modelsKnowledge of emerging technology validation approachesExperience with data visualization tools (e.g., Looker) for monitoring and reportingWhy Block? At Block, you'll be at the forefront of transforming how we approach model risk management through automation. Your work will not only ensure the reliability and safety of our machine learning systems but will also create lasting impact by building the tools and frameworks that will shape the future of model validation. This is a unique opportunity to combine technical expertise in machine learning, validation, and software development to create innovative solutions in the fintech space.We value diversity of perspectives because they fuel creativity and innovation. We offer competitive compensation packages, benefits, and perks, along with opportunities for career growth and professional development. As a Data Scientist in Model Risk Management at Block, you will be part of a team that is committed to providing reliable and accurate decision-making support while minimizing risk and delivering long-term value to the organization and its stakeholders.If you are passionate about using your quantitative and technical skills to make an impact on economic empowerment while building the future of model validation, join us at Block!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.Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.Zone A : $163,600 — $245,400 USDZone B : $155,400 — $233,200 USDZone C : $147,300 — $220,900 USDZone D : $139,000 — $208,600 USDEvery 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.#J-18808-Ljbffr

Salary : $139,000 - $208,600