Quantitative Researcher - Machine Learning in London

Quantitative Researcher - Machine Learning in London

London Full-Time 70000 - 90000 £ / year (est.) No working from home possible
Dormont Manufacturing Co

At a Glance

  • Tasks: Research, design, and deploy cutting-edge ML models for real-world applications.
  • Company: DRW, a leading trading firm with a focus on innovation and technology.
  • Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
  • Other info: Collaborative culture that values integrity, curiosity, and challenging the status quo.
  • Why this job: Join a dynamic team and make an impact in the fast-paced world of finance.
  • Qualifications: PhD or exceptional MSc in ML or related field with strong practical experience.

The predicted salary is between 70000 - 90000 £ per year.

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it’s how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

The Machine Learning Researcher will have a deep understanding of the principles behind modern ML algorithms — including recent advances such as transformer-based architectures and other state-of-the-art frameworks — and the ability to turn that knowledge into high-impact, production-ready solutions. The role involves applying advanced ML techniques to a wide range of forecasting challenges, building scalable ML pipelines, and deploying them in production, while working with high-dimensional, noisy, structured and unstructured datasets. Experience applying ML models in financial markets is desirable, but exceptional candidates with a strong ML background from tech, startups, or academia will also be considered.

Responsibilities

  • Research, design, and deploy robust ML models.
  • Build and maintain scalable, production-level ML pipelines.
  • Extract signals from large, noisy, real-world datasets.

Qualifications

  • PhD (or exceptional MSc) in ML, Computer Science, or related field.
  • Deep theoretical and practical knowledge of core ML algorithms, and comfortable experimenting with model architectures, feature engineering, and hyperparameter tuning to produce high-performance and resilient models.
  • Proven experience taking ML models from research to live production.

Quantitative Researcher - Machine Learning in London employer: Dormont Manufacturing Co

At DRW, we pride ourselves on being an exceptional employer that fosters a culture of innovation and integrity. Our Chicago headquarters offers a dynamic environment where talented individuals can thrive, with ample opportunities for professional growth and the autonomy to explore cutting-edge machine learning applications in financial markets. Join us to be part of a team that values curiosity and collaboration, while working on impactful projects that shape the future of trading.

Dormont Manufacturing Co

Contact Details:

Dormont Manufacturing Co Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Quantitative Researcher - Machine Learning in London

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 Dormont Manufacturing Co!

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 Quantitative Researcher - Machine Learning at Dormont Manufacturing Co.

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 Dormont Manufacturing Co.

Apply Directly through Our Website

When you find a suitable opening like Quantitative Researcher - Machine Learning at Dormont Manufacturing Co, 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 Quantitative Researcher - Machine Learning in London

Machine Learning Algorithms
Transformer-based Architectures
ML Model Deployment
Scalable ML Pipelines
Data Extraction from Noisy Datasets
Feature Engineering
Hyperparameter Tuning

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 Dormont Manufacturing Co, 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 Dormont Manufacturing Co. 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 Dormont Manufacturing Co

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 Dormont Manufacturing Co!

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.