At a Glance
- Tasks: Develop quantitative methodologies for historical market data and support risk management processes.
- Company: Join Deutsche Bank's innovative Market Data Strategy team in a hybrid role.
- Benefits: Gain valuable experience in a leading financial institution with a focus on professional growth.
- Other info: Inclusive workplace committed to diversity and a supportive environment.
- Why this job: Make an impact in market risk management while collaborating globally with experts.
- Qualifications: Strong Python skills and 3-5 years in quantitative modelling or market risk required.
The predicted salary is between 60000 - 80000 £ per year.
- On behalf of Deutsche Bank, we are looking for a
- Time Series Modeler for a
- 6 Month contract based in
- London (Hybrid)
The Role & Responsibilities
We are seeking a
Time Series Modeler with strong quantitative modelling expertise to join the Market Data Strategy team.
This role sits within Market Risk Management and is focused on developing robust historical market data used for Value at Risk (Va R), stress testing and economic capital calculations.
- Develop quantitative methodologies to construct historical market data time series for use in risk management.
- Build robust proxy models to backfill incomplete market data histories, particularly within energy markets.
- Apply time series modelling and statistical techniques to fill data gaps and create reliable historical datasets.
- Identify relationships between market variables to support proxy construction and validation.
- Ensure methodologies align with internal risk management standards and governance frameworks.
- Support the production of market data used in Value at Risk (Va R), stress testing and economic capital calculations.
- Work closely with the Head of Methodology to develop and enhance modelling approaches.
- Collaborate with global colleagues in London and Mumbai on data analysis, model development and implementation.
- Document methodologies and contribute to ongoing model governance and validation activities.
Key Accountabilities, Skills & Experience
Strong Python programming skills for data analysis and model development.
- 3–5 years’ experience in a quantitative modelling, market risk or market data role.
- Strong experience in time series modelling, statistical analysis and historical data construction.
- Experience developing proxy methodologies and applying gap-filling techniques to incomplete datasets.
- Good understanding of quantitative modelling techniques and the ability to identify relationships across market data.
- Good understanding of energy markets and energy market data.
We welcome applications from talented people from all cultures, countries, races, genders, sexual orientations, disabilities, beliefs, and generations and are committed to providing a working environment free from harassment, discrimination and retaliation.
This client will only accept workers operating via a PAYE engagement model.
AMS’s payroll service is in partnership with Giant; if you are successful in your application for this role, your contract will be via Giant.
For more information on Giant, please follow this link
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Contact Details:
Deutsche Bank AG, Frankfurt am Main Recruitment Team
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