At a Glance
- Tasks: Analyse orderbook data to uncover trading patterns and develop predictive models.
- Company: Join a rapidly growing proprietary trading firm with a global presence.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborate with experienced researchers and traders in a dynamic environment.
- Why this job: Dive into the world of finance and make an impact with your analytical skills.
- Qualifications: 1-3 years experience with orderbook data and a strong background in quantitative fields.
The predicted salary is between 50000 - 60000 £ per year.
Founded 20 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser.
We're looking for a Quantitative Researcher, focused on orderbook-driven signal generation. This role is ideal for someone early in their career who has hands‑on experience working with limit orderbook data and a genuine curiosity about how markets function at the tick level. You'll work closely with senior researchers and traders to develop, test, and refine predictive signals and models that inform trading decisions.
Responsibilities:
- Analyse high-frequency limit orderbook data to identify patterns, inefficiencies, and predictive signals
- Build and backtest quantitative models using historical tick and orderbook data
- Collaborate with senior researchers and traders to translate research findings into production‑ready strategies
- Develop and maintain data pipelines for processing large‑scale, high‑frequency market data
- Apply statistical and machine learning techniques, particularly tree‑based methods, to improve signal quality
- Continuously monitor and iterate on live signals and models based on performance
Requirements:
- 1–3 years of professional or research experience working directly with orderbook / limit order book (LOB) data
- Technical degree/background in a quantitative field (Math, Statistics, CS, Physics, Engineering, Financial Engineering)
- Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)
- Genuine interest in financial markets and market microstructure — you follow markets, not just models
- Solid foundation in statistics and quantitative analysis
- Strong problem‑solving skills and intellectual curiosity
- Ability to communicate technical findings clearly to non‑technical stakeholders
DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.
Quantitative Researcher employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher
✨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 Doist!
✨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 at Doist.
✨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 Doist.
✨Apply Directly through Our Website
When you find a suitable opening like Quantitative Researcher at Doist, 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
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 Doist, 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 Doist. 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 Doist
✨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 Doist!
✨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.
