At a Glance
- Tasks: Extract signals from vast datasets and collaborate across teams to enhance trading performance.
- Company: Leading market maker and hedge fund with a focus on innovation in ML and AI.
- Benefits: Competitive salary, substantial bonuses, work-life balance, and opportunities to attend conferences.
- Other info: Dynamic environment with opportunities for career growth and industry influence.
- Why this job: Join a top firm shaping the future of ML in finance and make a real impact.
- Qualifications: Extensive ML experience, strong programming skills, and excellent communication abilities.
Salary: £200k base + £150 - £400k bonus
Client: One of the world's top market makers is expanding their Machine Learning and related AI teams. Already a market-leader, in the past few years they have invested extensively in their data offerings and are ready to expand their ML and AI teams to stay ahead of the curve. A cross-asset liquidity provider, they do a huge volume of trades daily and are working with massive data sets that require enormous computational power.
Role: You’ll be extracting signals from vast datasets of market data to gain beneficial insights. Your time could be split between alpha generation in a trading team and time in the core engineering team - working very collaboratively as a firm to maximise PnL for the collective. For example, if you’re sat on an FX desk and find something useful, you’ll share the knowledge with the Equities team. You’ll be using ML to find ways to cut through the noise - how can you improve day-to-day performance with ML techniques? Is there AI assistance you can utilise to make everyone's life easier - from traders to operations, and ML tools for engineers?
Requirements:
- Extensive ML experience
- Strong programming skills in any OO language
- Collaborative nature with excellent communication skills
- Ability to balance pragmatism and great tech
Benefits:
- Shape the firm and, to an extent, the industry's ML developments
- Attend conferences
- Excellent compensation package
- Good work-life balance
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
Machine Learning Researcher at leading Market Maker / Hedge Fund employer: eFinancialCareers
Quilter plc is an exceptional employer, offering a dynamic work environment in Southampton where innovation and collaboration thrive. With a strong commitment to employee growth, comprehensive benefits including a generous holiday allowance and a non-contributory pension scheme, Quilter fosters a culture of inclusivity and continuous improvement, empowering employees to make meaningful contributions to the financial futures of their clients and communities.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Researcher at leading Market Maker / Hedge Fund
✨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 eFinancialCareers!
✨Show Off Your Projects
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 Machine Learning Researcher at leading Market Maker / Hedge Fund at eFinancialCareers.
✨Leverage Professional Networks
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 eFinancialCareers.
✨Apply Directly through Our Website
When you find a suitable opening like Machine Learning Researcher at leading Market Maker / Hedge Fund at eFinancialCareers, 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 Machine Learning Researcher at leading Market Maker / Hedge Fund
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 eFinancialCareers, 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 eFinancialCareers. 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 eFinancialCareers
✨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 eFinancialCareers!
✨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.
