Data Analyst

Company overview

Our client, a long-established, globally regulated financial and technology group, operates across multiple international markets and serves millions of users through advanced trading platforms and digital financial products. The business combines institutional-grade trading infrastructure with modern data and analytics capabilities, supporting high-volume, accuracy-critical decision-making across dealing, risk, and performance functions.

Role overview

This role sits close to the quantitative dealing function, working day-to-day with Quantitative Analysts and internal stakeholders to support reporting pipelines, production datasets, and analytical workflows. In addition to maintaining reporting outputs, the Data Analyst will validate trading and risk metrics, investigate discrepancies across data sources, and support continuous improvements to the analytical frameworks used in daily decision-making. It offers hands-on exposure to real trading data, risk management processes, and modern data infrastructure—well-suited to an early-career professional or recent graduate seeking growth in a quantitative dealing environment.

Responsibilities

• Monitor and validate daily and periodic reports to ensure accuracy, consistency, and alignment with agreed definitions and benchmarks.
• Perform first-level reconciliation and discrepancy analysis across multiple data sources, identifying root causes and documenting findings.
• Maintain reporting datasets and support updates to filters/parameters, validating changes prior to release.
• Contribute to the quality, completeness, and reliability of data inputs used in risk management and hedging decisions.
• Use Excel, SQL, and Python to extract, compare, and analyze structured datasets for reporting and reconciliation.
• Support backtesting and verification of existing risk management and dealing algorithms, assessing behavior across historical periods and different scenarios.
• Document reporting logic, data assumptions, and procedural changes to improve transparency and reduce recurring discrepancies.
• Collaborate with Quantitative Analysts, dealers, and internal stakeholders to ensure smooth daily operations and data-driven decision-making.
• Gain exposure to cloud-based data and analytics services, contributing to scalable and increasingly automated workflows.

Requirements

• Strong attention to detail and a methodical approach to working with data in accuracy-critical environments.
• Basic working knowledge of Python for data analysis and manipulation.
• Basic to intermediate SQL skills for querying and validating structured datasets.
• High proficiency in Excel, including formulas, reconciliation methods, and structured analysis.
• Ability to work across multiple data sources and identify inconsistencies, anomalies, and potential data quality issues.
• Strong motivation to learn, take ownership of tasks, and develop technical skills through hands-on exposure.
• Good communication skills, with the ability to clearly document findings and explain outcomes to technical and non-technical stakeholders.
• Bachelor’s degree (preferred) in Data Science, Statistics, Economics, Finance, or a related quantitative discipline.
• Genuine interest in trading and financial markets is an advantage.