London‑based (City location)
4 days onsite / 1 day from home
£175/day via PAYE (holiday pay, sick pay & pension included)
We are supporting our client, a global market‑leading financial information & research organisation, known for its high‑calibre analytics teams and advanced data environment. They are expanding their European energy analytics capability and require a data‑driven analyst to support their gas‑market research function during a maternity cover period.
This role sits within a specialist European gas analytics group, contributing to the modelling, scripting and data‑quality foundations behind their energy‑market insights. Although the team covers gas‑market fundamentals, previous experience in the gas or LNG sector is not mandatory but rather desirable. What matters most is strong Python capability, comfort with complex datasets, and the ability to collaborate with analysts to improve forecasting tools and workflows.
This is a highly hands‑on position where you’ll refine models, enhance scripts, test data processes, and help shape analytical outputs in a fast‑paced, intellectually curious environment.
Essential Skills
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Strong Python coding experience, including testing, debugging and improving existing scripts.
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Ability to work confidently with large, multi‑source datasets — cleaning, validating and structuring data.
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Familiarity with statistical or time‑series techniques (forecasting, regressions, pattern identification).
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Strong analytical mindset, able to challenge assumptions and extract meaningful insights from noisy data.
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Clear communication skills and the ability to work closely with subject‑matter experts.
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Excellent problem‑solving ability and a proactive, curious approach.
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No prior gas‑market or energy‑sector experience required — open to analysts from any data‑focused background.
Responsibilities
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Maintain, refine and run forecasting models for European gas‑market fundamentals.
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Improve existing Python scripts and develop new ones to support analytical workflows.
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Ensure data quality, structure and consistency across various datasets used in forecasting.
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Provide quantitative insight and technical input to ongoing analytical work.
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Assist with process mapping, documentation and continuous improvement initiatives.
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Conduct rigorous testing, debugging and optimisation of analytical tools and scripts.