Company description:

Our client is a leading global bank with a prominent Center of Excellence in Krakow. This isn't just any bank; it's one of the institutions that significantly impact the global stage and one that we can all be proud to be associated with.

Manager - Treasury Analytics

Responsibilities:

- Use statistical modelling and machine learning techniques to develop prepayment/pipeline models for mortgage products to hedge the risk and assess the IRRBB risk metrics.
- Develop the required behavioural models for different products to assess the IRRBB risk metrics.
- Use the quantitative expertise to design models supporting the Markets Treasury business and other functional Treasury teams where required. Proactively build tools in Python to test the proposed models, to formulate requisite analysis and to measure the impacts of model change.
- Work together with Financial Engineering and IT teams to contribute in the development of the One Treasury Platform.
- Understand both regulatory and business requirements, ensuring that the models are fit-for-purpose.
- Be responsible for Model Life Cycle - starting from defining the objectives to model development / testing, model documentation, on-going model assessment and validation as well as internal & regulatory scrutiny.
- Coordinate projects focusing on ensuring consistency across sites. Identify areas for efficiency improvements, automation and enhanced controls in existing processes. Document proposed changes and agree with the onshore process team prior to implementation. Document all process changes and improvements to reflect the latest process.
- Be able to clearly explain model details to other areas of the bank in non-technical language, and assisting in the on-going usage of these models in a day-to-day setting, e.g. helping to explain significant model value changes.

Requirements:

- Academic background in a quantitative field such as Mathematics or Physics.
- Qualification and Expertise in mathematics / statistics / machine learning algorithms.
- 3+ years of relevant experience, experience in designing behavioural models.
- Solid background in object-oriented computer programming - ideally in Python, preferably in large scale financial or technical computations.
- Good understanding of the Banking Book risks: IRRBB risk components and liquidity risks.
- Familiarity with financial assets and liabilities, with a preference for experience with asset pricing and metrics used to govern financial institutions, e.g. liquidity coverage ratios, balance sheet and capital ratios.
- Experience with financial markets, with a preference for vanilla interest rate derivative pricing, bond products pricing, curve construction, hedging strategies and risk management.

The offer:

- Multisport
- Medical care
- Bonuses
- Flexible working hours
- Life insurance