At a Glance
- Tasks: Design and implement core functionality in C++ and Python for innovative financial tools.
- Company: Deutsche Bank AG, a leading global bank with a focus on innovation.
- Benefits: Competitive salary, pension, generous holiday, healthcare, and hybrid working options.
- Why this job: Join a dynamic team to create impactful solutions in finance using cutting-edge technology.
- Qualifications: Experience in C++ and Python, with a passion for analytics and collaboration.
The predicted salary is between 70000 - 90000 £ per year.
Deutsche Bank AG is seeking a Core Quantitative Strategic Analytics Developer in London.
You will design and implement core functionality in C++ and Python for the Kannon platform, focusing on low-latency, cross-asset valuation, risk and P&L tooling.
The role involves working with Strats, traders and quants to deliver robust, scalable solutions with modern CI/CD practices.
The position offers hybrid working, a competitive salary, pension, generous holiday, healthcare and a range of flexible
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Strategic Analytics Developer – Core Quant (C++/Python) employer: Deutsche Bank AG
Deutsche Bank is an exceptional employer, offering a dynamic work culture in Birmingham that prioritises employee well-being and professional growth. With a hybrid working model, competitive salary, and comprehensive benefits including private healthcare and generous holiday allowances, employees are empowered to thrive both personally and professionally while contributing to the vital mission of combating financial crime.
StudySmarter Expert Advice🤫
We think this is how you could land Strategic Analytics Developer – Core Quant (C++/Python)
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We think you need these skills to ace Strategic Analytics Developer – Core Quant (C++/Python)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Deutsche Bank AG, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Deutsche Bank AG. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Deutsche Bank AG
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Deutsche Bank AG!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
