Data Analyst

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.,

• 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
  
  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
  
  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