Quantitative Analyst – FCP Model Validation| SEB, Vilnius at seb

<div> <p>SEB is a leading Northern European financial services group with a strong focus on risk identification, measurement, monitoring, and governance. As banking becomes increasingly data‑driven and model‑intensive, model validation plays a critical role in ensuring trust, regulatory compliance, and sound decision‑making.</p> <p><strong>About the role: </strong></p> <p>As part of an independent Model Validation function, you will challenge model design, data, and outcomes, and turn your findings into clear recommendations for stakeholders and senior management. We are now strengthening our Model Risk function in Vilnius and are looking for a talented Quantitative Analyst to join our Financial Crime Prevention (FCP) Model Validation team.</p> <p>You will join an experienced, highly analytical Model Validation team and independently assess financial crime models, including money laundering (ML)/terrorist financing (TF) transaction monitoring, customer risk scoring, and related models—using statistical testing, benchmarking, and outcome analysis to challenge model performance and limitations. Your work supports regulatory compliance, risk management, and key business decisions across SEB.</p> </div> As a Quantitative Analyst, you will be responsible for: • Performing independent qualitative and quantitative validation of financial crime risk models, covering model design, data, methodology, implementation, and use • Assessing model performance using statistical testing, benchmarking, sensitivity analysis, and outcome analysis • Evaluating data quality, assumptions, limitations, and sources of model risk • Translating complex quantitative results into clear insights and actionable recommendations for senior management and model stakeholders • Contributing to the continuous development and automation of the FCP Model Validation framework, tools, and methodologies • Preparing high-quality validation reports aligned with regulatory expectations • Collaborating closely with model developers, model owners, compliance, and risk stakeholders across the Nordics, Baltics, and other countries where SEB Group operates To thrive in this role, we believe you have: • Strong academic background in mathematics, statistics, econometrics, data science, engineering, physics, finance, or a related quantitative field. • Solid experience working with data and quantitative analysis (e.g. R or Python, SQL, Git). • Interest in model validation, model risk, and the regulatory use of models. • Ability to critically assess models and data. • Strong analytical mindset combined with the ability to clearly explain results to non‑technical audiences. • Proactive, independent, and quality‑driven team player. • Previous experience in ML/TF, financial crime, risk management, or regulated financial services is an advantage but not a requirement. What we offer: • A key role in an independent Model Risk function with high visibility and impact. • Exposure to a wide range of financial crime risk models across SEB Group. • A strong learning environment with continuous development in quantitative methods, regulation, and model risk management. • Flexible hybrid working model and focus on work–life balance. • Attractive benefits package and additional days off. • Inclusive, international, and value‑driven work culture. Do you want to be a part of SEB? Welcome to our inclusive culture, where our shared values inspire and uplift our team. We celebrate diversity and strive to ensure every employee feels seen, heard, and valued. We are looking forward to your application by May 5, 2026. Since we select candidates continuously, feel free to send in your application before the deadline. Learn more about working at SEB here: [Upgrade to PRO to see link] It is our fundamental belief that inclusion and diversity is crucial for our future success. We strive to have an inclusive, value-driven culture where employees feel valued, respected, and involved irrespective of who they are, what they believe or where they come from. #GSV