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
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.
Key responsibilities of the role include:
- 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
Who are we looking for?
The ideal candidate will have the following skills and experience:
- 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
- A collaborative approach to working with stakeholders
- An 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
Why join us?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (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 schemeMonthly company events
.
#J-18808-Ljbffr…