At a Glance
- Tasks: Transform raw data into actionable insights while collaborating with top-tier researchers.
- Company: Join a leading quantitative finance firm that values innovation and collaboration.
- Benefits: Competitive pay, generous leave, healthcare, and exciting team outings.
- Other info: Dynamic culture with a focus on diversity and career growth.
- Why this job: Shape the future of finance using cutting-edge technology and AI.
- Qualifications: Strong academic background in quantitative subjects and solid Python skills.
The predicted salary is between 56700 - 69300 £ per year.
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.
From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve.
Together we’re building a world-class platform to amplify our teams’ most powerful ideas.
As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.
Take the next step in your career.
The role Quantitative Data Engineers take data from its raw source through to live signals, working alongside Quantitative Researchers at each step in between.
We are using large language models to automate and scale this process, so that we can take on more data than any team could handle by hand.
The work is already underway.
You will work in Python on large-scale compute and industry-leading infrastructure, with access to leading internal and external models.
AI is part of how every team here works, accelerating thinking and delivering impact.
All colleagues are expected to bring AI into their daily workflows.
Key responsibilities of the role include
- Onboarding new third-party datasets, building the pipelines, normalisation and validation that make them research-ready
- Partnering with Quantitative Researchers to engineer features and build signals from onboarded data
- Using LLM-based agents and workflows to safely automate the pipeline from ingestion to signals
- Building tools and reusable workflows that help researchers and data scientists scale their work
Who are we looking for?
- A strong academic record, including a minimum 2:1 degree or equivalent in a quantitative subject such as mathematics, statistics, computer science, physics or engineering
- A combination of strong software engineering and data skills
- Solid knowledge of algorithms, data structures and software fundamentals
- Experience building production data pipelines, with strong Python data processing skills
- Comfort applying probability and statistics to real-world data problems
- Motivation from seeing your work deliver measurable value
- A preference for highly collaborative environments that value innovation, proactivity and flexibility
- Hands-on experience of LLM-based agents and workflows is desirable
- You don't need to have all of the above to apply. Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 35 days' annual leave
- 9% company pension contributions
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- Cycle-to-work scheme
- Monthly company events
- Experience days: all-expenses-paid, bucket-list outings with colleagues, from Michelin-star tasting menus to European day trips.
We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best.
If you have a disability or special need that requires accommodation please let us know in the relevant section.
At G-Research, we are passionate about the intersection of finance, technology, and the future.
We offer a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.
We are proud to employ some of the best people in their field and to nurture their talent in our collaborative working environment.
Quantitative Data Engineer employer: Barlowe LLP
G-Research is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. With a strong focus on employee growth, we provide ample opportunities for professional development and hands-on experience with cutting-edge technologies. Our culture fosters teamwork and creativity, making it an ideal place for those looking to make a meaningful impact in the field of network engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Data Engineer
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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 Barlowe LLP.
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We think you need these skills to ace Quantitative Data Engineer
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 Barlowe LLP, 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 Barlowe LLP. 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 Barlowe LLP
✨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!
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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 Barlowe LLP!
✨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.
