Data Analyst SQL Python - Hedge Fund

Client Server
Greater London, England
13 months ago
Applications closed

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Posted
8 Aug 2025 (13 months ago)

Data Analyst (SQL Python) London / WFH to £80k

Do you have a first class education combined with a strong interest in quantitative trading?

You could be joining a specialist Hedge Fund and working on long term strategic projects which involve implementing quantitative statistical models that are used to forecast elements of demand and supply of energy for US markets.

As a Data Analyst you will research drivers of global gas prices and develop best-in-class supply and demand models to support decision making, partnering with experienced Quants and liaising with Portfolio Managers to deliver bespoke statistical models and methods, effectively communicating views and findings to traders, analysts and other stakeholders.

You'll actively contribute to the team wide fundamental analytics, maintaining best practice in team's Python libraries and dashboards and seeking continual improvement of data sources and the team's technical capabilities.

Location / WFH:

You'll be working in a collegiate team environment based in London with a small group of accomplished software / data engineers and finance entrepreneurs on a fulltime basis (Monday to Friday).

About you:

You have an excellent academic record of achievement; 2.1 or above at BSc, likely to have studied MSc / PhD level at a top tier university (Advanced Mathematics, Probability, Statistical Patterns) combined with commercial experience You have strong Python and SQL coding skills You're comfortable working with large data sets You have experienced of implementing highly scalable, performant, low latency solutions You have excellent written and verbal communication skills

What's in it for you:

Up to £80k + significant bonus Pension (8% non-contributory) Private Medical Insurance Life Assurance Training and career development opportunities Work from Home (x1 day London office per week) Company retreats such as Winter skiing trips and Summer weekends away

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