Quantitative AML Analyst

SEB is a leading northern European financial services group with a high focus on risk identification, measurement, monitoring, and governance. Banking is changing rapidly, and our highly skilled international quant team is committed to innovation, quality, and development of risk culture. Does that sound like a fit for you?

You will be part of a diverse, fast-growing, and professional team within the Model Risk function that ensures the quality of models used for measuring various risks. We conduct in-depth reviews of the models to ensure quality performance by assessing model design, modeling methodologies, regulatory compliance, implementation, and usage. We present insights and propose recommendations to the management and work closely with model developers, owners, users, and other key stakeholders.

In light of the increased attention to managing AML-related risks and the changing regulatory environment, you will take part in AML model validation framework development and automation of the validation processes to ensure comprehensive and informative analyses. You will be retrieving, analyzing, and interpreting data from various sources. You will have the empowerment to organize your work individually and introduce new and/or improve existing validation tools. Nevertheless, you will also be able to count on your colleagues to help you when needed. In addition, other financial crime prevention and risk areas falls under the scope of the team you will be a part of opening a door to wide variety of different interesting models.

Our team is located in Warsaw and Vilnius and you will work in close interaction with experienced professionals in Model Risk across Nordic and Baltic countries and communicate with key stakeholders from other sites within SEB globally. Do not worry, you do not need to relocate to Vilnius. You will work from the local office in Poland.

Developing financial crime prevention and risk models validation framework, procedures, and tools.

Assessing risks related to model design, data, output, and governance.

Testing financial crime prevention and risk models' quantitative performance.

Interpreting results of the tests performed and providing insights.

Consolidating your analysis in interactive reports.

Making recommendations on improving the control environment.

Presenting validation results.

An academic background in mathematics, statistics, econometrics, data science, finance, physics, engineering, or similar.

Good data handling (SQL) and intermediate statistical/programming knowledge (R/Python).

Willingness to take on ownership and deliver good quality work on time.

Proactive and constructive team player, ready to share experience and ideas.

Writing and communication skills (English is the main working language).

Work experience in the AML or other financial crime areas, working for a financial institution or consulting firm, machine learning skills would be treated as an advantage.

Different seniority levels are acceptable.