At a Glance
- Tasks: Join us to build models and automate risk processes in a dynamic environment.
- Company: Be part of a leading bank focused on quantitative risk analytics.
- Benefits: Gain hands-on experience, mentorship, and exposure to diverse risk disciplines.
- Other info: Diversity is key; we welcome applicants from all backgrounds.
- Why this job: Make an impact by contributing to innovative risk management projects.
- Qualifications: Master’s degree in a quantitative field and strong programming skills required.
The predicted salary is between 20000 - 30000 £ per year.
Purpose of Job
Under the supervision of the Principal and/or Associate Director, Quantitative Risk Analytics (QRA), the prospective intern will focus on specific quantitative risk modelling and development projects.
The intern will be responsible for the automation of some of the team’s credit and market risks processes and will participate in the implementation of the in‑house Quantitative Risk Engine (QRE).
The internship provides hands‑on exposure to quantitative risk management activities across market, credit and liquidity risk disciplines.
Depending on business priorities and individual performance, the intern may support the production of risk measures, development of risk analytics, process automation initiatives and implementation of quantitative methodologies used by the Bank.
No prior professional experience is required; however, candidates are expected to demonstrate strong quantitative and programming skills in a risk modelling context, with pricing financial instruments, statistical estimation and optimization methods.
The successful candidate will be expected to progressively assume responsibility for specific quantitative analyses, automation initiatives and risk management processes under the guidance of the QRA team.
High‑performing interns may have the opportunity to contribute to strategic quantitative risk initiatives and gain experience across multiple risk disciplines.
- Accountabilities & Responsibilities
- Contribute to the implementation of quantitative methodologies on derivatives pricing, risk factor calibration and simulation, market data processing and portfolio analytics and reporting.
- Support the development, testing and maintenance of quantitative risk models and analytical tools.
- Assist with automation and enhancement of market, credit and liquidity risk processes.
- Contribute to data analysis, quality controls and production activities supporting risk measurement and reporting.
- Participate in the development and testing of the Quantitative Risk Engine (QRE) and associated analytics infrastructure.
- Knowledge, Skills, Experience & Qualifications
- Master’s degree (or currently completing a Master’s degree) in Quantitative Finance, Mathematics, Statistics, Physics, Engineering, Computer Science or another highly quantitative discipline.
- Strong quantitative, analytical and programming skills.
- Ability to explain complex quantitative concepts in an accessible way and proven English language drafting skills.
- Familiarity with options pricing theory, stochastic processes, Monte Carlo simulation, optimization methods and statistical estimation.
- Basic understanding of major capital markets instruments across asset classes, notably with respect to derivatives (including credit derivatives and hybrids).
- Demonstrated programming ability in Python and/or C++ through academic projects, internships or research assignments. Familiarity with SQL would be advantageous.
- Familiarity with software development practices, version control systems (e. g. Git) and testing methodologies would be advantageous.
- Exposure to data analytics, reporting or quantitative risk platforms would be advantageous.
- Competencies & Personal Attributes
- Ability to analyse large datasets and investigate anomalies using quantitative and statistical techniques.
- Ability to work to deadlines and under time pressure.
- Attracted to the multicultural environment of EBRD as well as to the mission of the Bank with its challenges and opportunities.
Diversity is one of the Bank’s core values which are at the heart of everything it does.
As such, the EBRD seeks to ensure that everyone is treated with respect and given equal opportunities and works in an inclusive environment.
The EBRD encourages all qualified candidates who are nationals of the EBRD member countries to apply regardless of their racial, ethnic, religious and cultural background, gender, gender identity, sexual orientation, age, socio‑economic background or disability.
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Quant Risk Analytics Intern – Build Models & Automation in London employer: EBRD
The EBRD in Greater London is an exceptional employer, offering a dynamic hybrid work environment that fosters diversity and inclusion. Employees benefit from a strong commitment to professional development, with ample opportunities for growth within the financial services sector, all while contributing to a meaningful mission of enhancing operational risk governance across the organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Quant Risk Analytics Intern – Build Models & Automation in London
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Quant Risk Analytics Intern – Build Models & Automation in London
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at EBRD will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at EBRD
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress EBRD.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show EBRD that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
