ML Researcher β€” Quant Finance, End-to-End Impact (London) in England

ML Researcher β€” Quant Finance, End-to-End Impact (London) in England

England Full-Time 43200 - 72000 Β£ / year (est.) On-site
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At a Glance

  • Tasks: Lead the research lifecycle in machine learning for trading models.
  • Company: Top capital markets firm in London with a flat structure.
  • Benefits: Competitive salary, strong resources, and impactful work.
  • Why this job: Make a real difference in options trading with your ML expertise.
  • Qualifications: Masters or PhD in a quantitative field and Python proficiency.

The predicted salary is between 43200 - 72000 Β£ per year.

A leading capital markets firm in London is seeking a Machine Learning Researcher to own the research lifecycle from hypothesis to deployment. Applicants should have a Masters or PhD in a quantitative field, strong expertise in machine learning, and proficiency in Python. The role offers the opportunity to develop models that have a direct impact on trading in options markets, supported by robust resources and a flat organizational structure.

ML Researcher β€” Quant Finance, End-to-End Impact (London) in England employer: Citadel Securities

Citadel Securities is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. With a strong focus on employee growth, you will have access to cutting-edge technology and the opportunity to work alongside industry leaders in the fast-paced crypto market. Our commitment to engineering excellence ensures that you will be part of a team that values your contributions and fosters professional development.

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Contact Details:

Citadel Securities Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land ML Researcher β€” Quant Finance, End-to-End Impact (London) in England

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Citadel Securities!

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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like ML Researcher β€” Quant Finance, End-to-End Impact (London) at Citadel Securities.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Citadel Securities.

✨Apply Directly through Our Website

When you find a suitable opening like ML Researcher β€” Quant Finance, End-to-End Impact (London) at Citadel Securities, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace ML Researcher β€” Quant Finance, End-to-End Impact (London) in England

Machine Learning
Python
Quantitative Analysis
Model Development
Research Lifecycle Management
Hypothesis Testing
Deployment Skills

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Citadel Securities, 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 Citadel Securities. 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 Citadel Securities

✨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!

✨Showcase Your Projects

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 Citadel Securities!

✨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.