At a Glance
- Tasks: Own data integrity and improve workflows in a dynamic finance environment.
- Company: Join G-Research, a leader in quantitative finance with a collaborative culture.
- Benefits: Competitive pay, 35 days leave, free lunch, and a barista bar.
- Other info: Enjoy a flexible dress code and excellent work/life balance.
- Why this job: Make an impact by shaping tools that drive high-impact research.
- Qualifications: Strong SQL and Python skills, plus a collaborative mindset.
The predicted salary is between 60000 - 80000 £ 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.
The role Reference Data underpins G-Research’s trading and research workflows by curating core market datasets. As a Data Analyst, you will own day‑to‑day data integrity and investigate anomalies end to end. You will partner with engineers and stakeholders to improve pipelines, controls and downstream usability. This is a highly stakeholder‑facing role requiring proactive communication, accountability and strong teamwork.
Responsibilities
- Owning daily data quality across reference data products including instruments, corporate actions, calendars, pricing and identifiers.
- Designing and maintaining data quality checks, dashboards and alerting.
- Leading root cause analysis on incidents including trace lineage, identifying failure modes and driving remediation with engineering.
- Communicating proactively with stakeholders, setting expectations and explaining impact, severity and timelines.
- Driving issues to closure through clear ownership, tracking actions, validating fixes and preventing regressions.
- Contributing as a strong team player by documenting learnings, sharing context and improving team standards.
Qualifications
- Strong SQL skills.
- Strong Python skills for dataframe analytics using pandas or polars.
- Confident use of AI coding assistants with sound judgment and validation.
- Financial markets domain knowledge.
- Collaborative approach to working with stakeholders.
- Automation‑first mindset to reduce RTB and eliminate recurring manual work.
Nice to have:
- Familiarity with Git, notebooks and reproducible analytics practices.
- Experience working with engineers in modern deployment environments such as containers or Kubernetes.
Benefits
- 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.
Inclusivity
G‑Research is committed to cultivating and preserving an inclusive work environment. 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.
Data Analyst employer: Barlowe LLP
At G-Research, we pride ourselves on being an exceptional employer, offering a dynamic work environment in the heart of London where innovation thrives. Our commitment to employee growth is evident through our comprehensive benefits package, including competitive compensation, extensive annual leave, and a focus on work/life balance, all while fostering a culture of inclusivity and collaboration. Join us to be part of a world-class team that values your contributions and supports your professional development in the exciting field of quantitative finance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at events. Ask them about their experiences and any tips they might have for landing a role at G-Research.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and Python skills. Practice common data analysis scenarios and be ready to showcase your problem-solving abilities with real-world examples.
✨Tip Number 3
Show off your collaborative spirit! Be ready to discuss how you've worked with stakeholders in the past and how you can contribute to a team-focused environment at G-Research.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Analyst role. Highlight your SQL and Python skills, and any experience you have with financial markets. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how you can contribute to our team. Be sure to mention your collaborative approach and any relevant projects you've worked on.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled data integrity issues or improved processes in the past. We love seeing candidates who can think critically and drive issues to closure!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Barlowe LLP
✨Know Your Data Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss how you've used these tools in past projects, especially in relation to data integrity and quality checks. This will show that you can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific instances where you've identified and resolved data anomalies. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting your analytical thinking and root cause analysis abilities.
✨Communicate Like a Pro
Since this role involves a lot of stakeholder interaction, practice explaining complex data issues in simple terms. Think about how you would set expectations and communicate timelines effectively. This will demonstrate your proactive communication skills.
✨Emphasise Teamwork and Collaboration
Be ready to discuss how you've worked with engineers and other stakeholders in the past. Highlight your collaborative approach and any experiences where you contributed to team standards or documented learnings. This will show that you're a strong team player.
