At a Glance
- Tasks: Join a dynamic team to develop risk and PNL systems for credit trading.
- Company: Deutsche Bank, a leader in financial services with a focus on technology.
- Benefits: Competitive salary, 30 days holiday, private healthcare, and flexible benefits.
- Other info: Collaborative environment with excellent coaching and career growth opportunities.
- Why this job: Make an impact in finance using cutting-edge tech like AI and ML.
- Qualifications: 2+ years in a quant role, programming skills in C++/Python, and strong maths background.
The predicted salary is between 60000 - 80000 £ per year.
Position Overview
Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Bank’s businesses and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will join the quantitative credit Strats team working alongside Deutsche Bank’s European Flow Credit and Emerging Markets business. Our credit trading businesses are fully committed to technology as a key differentiator of performance and the partnership with quant strategists is seen as crucial to the future success of the desk.
You will be a member of a small agile team based in London delivering risk, profit and loss (PNL) and pre-trade flow and relative value analytics solutions to bond trading and sales. You will be a highly motivated self-starter and all-rounder with a working understanding of credit markets and the associated credit modelling mathematics, as well as being able to build production quality software applications and reports to tight timescales using appropriate technologies. You will be based on the trading floor and required to rapidly react to trader/sales/management demands in traditional ways but also using techniques in natural language processing (NLP) and machine learning (ML) and artificial intelligence (AI) to maximize our return on the large-scale data sets we curate.
What We’ll Offer You
- 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
- Development and support of daily risk and PNL systems
- Providing desk support to trading on live challenges and gathering requirements for potential solutions efficiently
- Implementing flow analysis management information systems (MIS) and reporting (e.g. volumes, market shares, hit rates, client profitability)
- Development of pre-trade analytics to support in trading decisions (e.g. computing trade relative value metrics and strategy backtesting)
- Provide quantitative modelling expertise to trading (e.g. portfolio optimization, flow matching, trade prospect ranking)
Your Skills And Experience
- 2+ years of experience in a front office technical/quant role within investment banking
- Proficiency in programming preferably C++/Python/kdb/java/javascript and in working with standard Software Development Lifecycle (SDLC) tools in a collaborative environment (git/bitbucket/JIRA etc.)
- Experience working with data, both in onboarding, cleaning and curating data in databases as well as analysis and presentation
- First degree in Maths/Natural Science/Computer Science/Engineering, PhD or Masters desirable. Some experience of machine learning and natural language processing a bonus
- Excellent interpersonal skills with the ability to collaborate and partner with various teams, and to be able to explain complex concepts effectively
How We’ll Support You
- Coaching and support from experts in your team
- A range of flexible benefits that you can tailor to suit your needs
- 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)
We welcome applications from all people and promote a positive, fair and inclusive work environment.
Credit Quant Strategist: PNL, Risk Analytics & ML in London employer: Deutsche Bank
Deutsche Bank is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets finance. With a strong commitment to employee growth, you will benefit from coaching by industry experts, flexible benefits tailored to your needs, and a culture that values diversity and inclusion. Join us to be part of a forward-thinking team that leverages cutting-edge technology and analytics to drive success in the credit markets.
StudySmarter Expert Advice🤫
We think this is how you could land Credit Quant Strategist: PNL, Risk Analytics & ML in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in credit quant roles. Attend meetups or webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning or risk analytics. This is your chance to demonstrate your coding prowess and analytical thinking. Share it during interviews or even on LinkedIn!
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills and quantitative concepts. Practice coding challenges and be ready to discuss your thought process. Remember, they want to see how you tackle problems, not just the final answer!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. Don’t forget to tailor your application to highlight your relevant experience in credit markets and analytics.
We think you need these skills to ace Credit Quant Strategist: PNL, Risk Analytics & ML in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your programming skills, especially in C++ or Python, and any relevant experience in quantitative roles. We want to see how you fit into our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about credit markets and how your background makes you a great fit for the role. Don’t forget to mention your experience with machine learning and NLP if you have it!
Showcase Your Projects:If you've worked on any relevant projects, whether in school or at work, make sure to include them. We love seeing practical applications of your skills, especially those that involve risk analytics or PNL systems. It shows us what you can bring to the table!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Deutsche Bank
✨Know Your Numbers
Brush up on your understanding of credit markets and the associated modelling mathematics. Be prepared to discuss specific metrics related to risk and PNL, as well as how you would approach developing pre-trade analytics.
✨Showcase Your Coding Skills
Since programming is key for this role, make sure you can demonstrate your proficiency in C++, Python, or Java. Bring examples of past projects where you've built production-quality software applications, and be ready to explain your thought process.
✨Understand the Business
Familiarise yourself with Deutsche Bank’s European Flow Credit and Emerging Markets business. Knowing how quant strategies impact trading decisions will help you articulate your value during the interview.
✨Communicate Effectively
Prepare to explain complex concepts in a simple way. Practice discussing your experience with machine learning and natural language processing, and think about how you can convey these ideas to non-technical stakeholders.
