Method Resourcing
Data Strat
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Method Resourcing are delighted to partner with a well-backed Financial Technology start-up HQed in the City looking to hire a (Junior) Data Strat to join their team as they continue to grow and expand their offering.
This role is ideal for someone with 1-3 years experience cleaning/standardising/validating financial data in a capital markets environment, or a recent graduate with a demonstrable interest in capital markets/derivatives.
This business are financially supported by some of the world's largest banks and have hugely impressive growth plans, whilst offering the opportunity to work alongside some of the leading talent in the FinTech world.
Responsibilities:
- Aggregate, clean, and standardize valuation data from client institutions
- Build and maintain Python-based data quality checks and validation rules
- Investigate anomalies, distinguish genuine market behavior from errors, and escalate with clear write-ups
- Help build and maintain an OTC securities universe across Rates, FX, Credit, Equity, and Commodities
- Support data issue analysis and help respond to queries from major investment bank clients
- Collaborate closely with senior data strats, engineers, and product stakeholders
- Contribute to documentation and data definitions for consistency and clarity
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About you:
- 0–3 years' experience. If you have 1–3 years, cleaning, standardizing, or validating financial data should have been the core of your role; at a data vendor, market data ops, fund administration, an index/benchmark provider, valuations ops, or middle office
- Recent graduates: at least one substantial internship or placement involving hands-on data cleaning or validation (finance-adjacent preferred), with evidence of careful, systematic work
- Strong Python skills, with pandas and numpy central to prior work, internships, or major projects- this will be tested in a coding interview
- Working knowledge of SQL (coursework or project use is fine for recent graduates)
- A solid numerate degree - maths, physics, engineering, quantitative economics/finance, or a data science conversion MSc. Institution prestige doesn't matter to us
- Exposure to financial markets or derivatives (academic or professional), and genuine interest in OTC derivatives across Rates, FX, Credit, Equity, and Commodities
- Comfortable handling complex, real-world datasets, with a genuine appetite for detailed, systematic work
- Clear written communication and willingness to engage with client-facing teams
- Willingness to learn modern software lifecycle management
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