Trading Data Analyst - Risk & Client Analytics

Company overview

Finalto operates globally as a provider of liquidity and trading technology for institutional and B2B markets. The company works across financial markets worldwide and is supported by regulated operations in the UK, Singapore, Cyprus, Australia, and the UAE, along with operational teams in Denmark and Bulgaria. Its offering combines multi-asset liquidity, risk management, and modern trading platforms designed to help clients grow more efficiently and sustainably.

As part of a broader financial services group, Finalto brings together the strength and stability of an established organisation with the speed and adaptability of a fintech business. The culture is built around collaboration, integrity, performance, and a strong focus on innovation, governance, and operational excellence. The company also emphasizes career development, international exposure, and the opportunity to contribute meaningfully to the evolution of trading technology and liquidity solutions.

Role summary

This London-based position is for a Trading Data Analyst focused on Risk & Client Analytics. The role sits at the intersection of trading, risk, analytics, data, and technology. The successful candidate will explore trading activity, client behaviour, execution outcomes, market data, and exposure patterns to help teams make better decisions.

This is an investigative analytics role rather than a standard reporting function. It calls for someone who can work with complex trading datasets, uncover patterns, explain client flow, and turn data into practical guidance on client segmentation, pricing, execution setup, liquidity management, hedging approach, and risk appetite.

Key responsibilities

• Study client trading behaviour, profitability, execution performance, order-flow characteristics, market impact, and risk exposure.
• Work across large trading and market datasets such as trade records, tick data, pricing information, execution logs, order flow, and client-level performance measures.
• Spot trends, unusual activity, behavioural shifts, concentration risks, and changes in client or product performance.
• Create analytical methods that improve understanding of client flow, trading patterns, execution results, and market-data behaviour.
• Provide analytical input for decisions on risk appetite, client segmentation, pricing, execution configuration, liquidity management, and hedging strategy.
• Develop and maintain dashboards, reports, and analysis tools that improve visibility into trading activity, execution quality, and trading risk.
• Use Python, SQL, Databricks, and related tools to pull, clean, transform, analyse, and visualise data.
• Automate recurring analysis, monitoring, and reporting tasks where possible.
• Partner with Data and Technology teams to strengthen data quality, pipelines, and analytical frameworks.
• Present findings in a clear way to both technical teams and non-technical stakeholders.

What the employer is looking for

• Hands-on experience in data analysis, trading analytics, risk analytics, execution analytics, market data, or another analytics-heavy environment.
• Strong command of Python and SQL.
• Working knowledge of Databricks or similar analytics platforms.
• Strong problem-solving ability with a high level of accuracy and attention to detail.
• Comfort working with large, complicated, and imperfect datasets.
• Good grasp of statistics, data visualisation, and performance analysis.
• Strong interest in financial markets, trading behaviour, execution quality, market microstructure, and client-flow analysis.
• Ability to turn complex data into clear, actionable recommendations for Risk, Trading, and senior leaders.
• Effective communication skills and confidence working across multiple functions.

Preferred experience and background

• Exposure to KDB/q, tick data, quote data, order lifecycle data, or high-frequency market data.
• Background in client-flow analysis, execution analytics, trading-pattern analysis, or market-data analytics.
• Familiarity with Java, C++, Streamlit, BI tools, dashboard development, or internal analytics applications.
• Experience with FX, CFDs, equities, futures, commodities, indices, crypto, or similar traded instruments.
• Understanding of trading concepts including spread, slippage, liquidity, latency, order flow, execution quality, client profitability, hedging, and risk exposure.
• Previous work in a broker, liquidity provider, market maker, hedge fund, bank, trading firm, e-trading business, or fintech setting.

Qualifications

A degree in Computer Science, Mathematics, Statistics, Engineering, Quantitative Finance, Data Science, or a related quantitative field is preferred. The role is ideally suited to candidates with about 2 to 5 years of relevant professional experience, though applicants with equivalent experience and strong capability may also be considered.

Additional information

No stipend or salary figure was provided. The job is a full-time, on-site role in the London Area, United Kingdom. No start date, application deadline, number of openings, or duration was specified.