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.
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:
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Owning daily data quality across reference data products including instruments, corporate actions, calendars, pricing and identifiers
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Designing and maintaining data quality checks, dashboards and alerting
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Leading root cause analysis on incidents including trace lineage, identifying failure modes and driving remediation with engineering
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Communicating proactively with stakeholders, setting expectations and explaining impact, severity and timelines
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Driving issues to closure through clear ownership, tracking actions, validating fixes and preventing regressions
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Contributing as a strong team player by documenting learnings, sharing context and improving team standards
The ideal candidate will have the following skills and experience:
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Strong SQL skills
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Strong Python skills for dataframe analytics using pandas or polars
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Confident use of AI coding assistants with sound judgment and validation
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Financial markets domain knowledge
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A collaborative approach to working with stakeholders
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An automation-first mindset to reduce RTB and eliminate recurring manual work
Nice to have
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Familiarity with Git, notebooks and reproducible analytics practices
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Experience working with engineers in modern deployment environments such as containers or Kubernetes
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Highly competitive compensation plus annual discretionary bonus
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Lunch provided (via Just Eat for Business) and dedicated barista bar
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35 days’ annual leave
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9% company pension contributions
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Informal dress code and excellent work/life balance
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Comprehensive healthcare and life assurance
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Cycle-to-work scheme
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Monthly company events
