Market Data Quant Specialist

You will be working in the MDSA team in MVRM. You will have the opportunity to work on high-impact projects supporting business growth and regulatory requirements through the delivery of market data time series. The team works with robust quantitative techniques to deliver reliable market data. You will contribute to projects that use machine learning/statistical techniques alongside strong quantitative finance concepts, to generate high quality historical market data and forecast trends.

You will work alongside experienced colleagues who will coach and support your development, helping you grow through exposure to a broad range of advanced statistics and machine learning techniques, domain-specific knowledge, and stakeholder-facing activities.

What we’ll offer you

A healthy, engaged and well-supported workforce are better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its centre.

You can expect:

• Hybrid Working - we understand that employee expectations and preferences are changing. We have implemented a model that enables eligible employees to work remotely for a part of their working time and reach a working pattern that works for them
• Competitive salary and non-contributory pension
• 30 days’ holiday plus bank holidays, with the option to purchase additional days
• Life Assurance and Private Healthcare for you and your family
• A range of flexible benefits including Retail Discounts, a Bike4Work scheme and Gym benefits
• The opportunity to support a wide ranging CSR programme + 2 days’ volunteering leave per year

Your key responsibilities

• Quantitative modelling of market risk data using machine learning and statistical techniques
• Developing proxy methodologies for risk factors across asset classes
• Data validation and forecasting
• Creating Prototypes and collaborating to take them through to successful deployment in production
• Design and implement market data framework compliant with principles of Fundamental Review of Trading Book (FRTB), supporting and working closely with Group Strategic Analytics (GSA), Quantitative Analysts, Risk Methodology and IT teams

Your skills and experience

• Educated to Masters/PhD degree in a numerate field (e.g. Quantitative finance, Math’s, Physics, Engineering) or equivalent experience
• Strong quantitative and Python coding skills including a good mastery of Probability, Statistics, Derivatives Pricing Theory
• Strong understanding of Market Risk framework underlying Pillar 1 and Pillar 2 models including new regulations (e.g. FRTB)
• Experience in designing system use cases, testing new methodologies
• Excellent written and oral communication skills

How we’ll support you

• Coaching and support from experts in your team
• A culture of continuous learning to aid progression
• We value diversity and as an equal opportunities’ employer, we make reasonable adjustments for those with a disability such as the provision of assistive equipment if required (e.g. screen readers, assistive hearing devices, adapted keyboards)

About us

Deutsche Bank is the leading German bank with strong European roots and a global network. Click here to see what we do.

Deutsche Bank in the UK is proud to be named in The Times Top 50 Employers for Gender Equality and has been awarded a Gold Award from Stonewall and named in their Top 100 Employers.

If you have a disability, health condition, or require any adjustments during the application process, we encourage you to contact our Adjustments Concierge on adjustmentsconcierge@db.com to discuss.

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.

Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.

We welcome applications from all people and promote a positive, fair and inclusive work environment.