4,392 Quantitative Analyst jobs in the United Kingdom

Senior Quantitative Analyst

Up to £130,000

London (Fully Onsite)

Please note: This role cannot provide sponsorship

Company:

Join a world-class global investment management firm that specialises in sports trading, spanning football, soccer, cricket, and major US sports like the NBA. As part of their elite trading team, you’ll harness advanced statistical techniques and machine learning to build predictive models that shape their trading strategies.

In this role, you’ll drive revenue growth and develop mathematical models to predict the outcomes of sports events.

Responsibilities:

• Utilise advanced statistical techniques and machine learning to build predictive models that shape our trading strategies
• Develop predictive models for sports outcomes using advanced mathematical and statistical techniques.
• Analyse real-world sports data to uncover patterns and generate insights that inform trading strategies.
• Implement and optimise numerical methods to support robust, scalable model performance in live environments.
• Collaborate closely with fellow researchers and developers in a fast-paced, science-driven team environment.
• Continuously innovate and improve modelling approaches to stay competitive in dynamic and data-rich sports markets.

Requirements:

• MSc, PhD Degree in Mathematics
• Have 5+ years of relevant industry experience.
• Strong coding skills in Python and SQL
• Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment.
• Strong background in mathematics, statistics, or a related quantitative field
• Experience in developing mathematical models to predict real-world outcomes
• Proficiency in numerical implementation and computational methods

Quantitative Analyst - Model Validation (Assistant Vice President Level)

About the Role

The primary mandate of the Model Validation team is to manage model risk across a broad range of business areas, including models used for derivatives valuation, market and credit risk management, liquidity, and capital computations. The team is responsible for independently reviewing models to ensure theoretical soundness, implementation accuracy, and appropriate use. The role involves evaluating model performance, identifying limitations, and helping stakeholders understand the associated risks.

Key Responsibilities

• Perform independent validation and approval of quantitative models, raising and managing model validation findings.
• Conduct annual reviews and revalidations of existing models.
• Provide effective challenge to model assumptions, mathematical formulations, and implementation methodologies.
• Assess and quantify model risk to inform stakeholders and contribute to compensating control development.
• Contribute to strategic and cross-functional initiatives within the Model Risk function.
• Oversee ongoing model performance monitoring, including benchmarking, process verification, and outcome analysis.
• Communicate validation results, model limitations, and uncertainties to stakeholders and management.
• Contribute to automation and efficiency initiatives, including applications of AI and process optimization.

Qualifications

• MSc or preferably PhD in a quantitative discipline (e.g., Physics, Mathematics, Computer Science, Financial Engineering, Statistics).
• Strong understanding of Value-at-Risk (VaR) computation frameworks and Counterparty Credit Risk (CCR) modelling.
• Experience in model validation or development, particularly within risk or liquidity modelling contexts.
• Proficiency in Python (preferred) or similar quantitative programming languages.
• Strong analytical and communication skills, with the ability to provide practical solutions to complex challenges.
• Demonstrated ability to work collaboratively within a team-oriented environment.

Additional Skills - Liquidity Modelling in Investment Banking

• Deep understanding of liquidity risk frameworks and internal liquidity stress testing (ILST) methodologies.
• Experience validating or developing liquidity models, including cash flow projections, liquidity coverage ratio (LCR), and net stable funding ratio (NSFR) frameworks.
• Familiarity with regulatory expectations for liquidity risk management (e.g., Basel III, PRA, FED, or ECB guidelines).
• Ability to assess model performance under stressed conditions and evaluate model assumptions around funding profiles, behavioral deposits, and contingency funding.
• Knowledge of balance sheet and treasury modelling, including funding concentration and intraday liquidity risk.
• Experience working with liquidity data, scenario analysis, and backtesting of liquidity models.
• Strong quantitative and programming skills for implementing and testing liquidity models efficiently.

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

• Develop, backtest, and implement quantitative models for trading strategies, pricing derivatives, and risk management.
• Analyze market data to identify trading opportunities and potential risks.
• Build and maintain robust data infrastructure and pipelines for quantitative research.
• Collaborate with traders, portfolio managers, and risk officers to understand business needs and provide analytical solutions.
• Validate model performance and ensure compliance with regulatory requirements.
• Develop tools and systems to automate trading execution and risk monitoring.
• Stay current with academic research and industry trends in quantitative finance and computational methods.
• Clearly document methodologies, assumptions, and results of quantitative analyses.
• Present complex quantitative findings to both technical and non-technical stakeholders.
• Contribute to the innovation and continuous improvement of the firm's quantitative capabilities.

• Master's or Ph.D. in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field.
• Proven experience as a Quantitative Analyst or in a similar quantitative role within the financial services industry.
• Expertise in statistical modeling, time-series analysis, machine learning, and stochastic calculus.
• Proficiency in programming languages such as Python, C++, or R, with strong data manipulation and analysis libraries.
• Experience with financial databases and market data platforms (e.g., Bloomberg, Refinitiv).
• Solid understanding of financial markets, derivatives, and risk management principles.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and interpersonal skills, with the ability to explain complex concepts clearly.
• Demonstrated ability to work independently and manage multiple projects in a remote environment.
• Attention to detail and a commitment to accuracy.

• Develop, implement, and back-test quantitative trading strategies.
• Build and maintain complex financial models for pricing, risk management, and portfolio optimization.
• Conduct statistical analysis of market data to identify trends and opportunities.
• Collaborate with portfolio managers and traders to refine investment strategies.
• Perform data mining and analysis on large datasets.
• Validate model assumptions and ensure the accuracy of analytical results.
• Prepare reports and presentations on quantitative findings for senior management.
• Stay current with advancements in quantitative finance and relevant technologies.
• Contribute to the improvement of data infrastructure and analytical tools.
• Ensure compliance with regulatory requirements and internal policies.

• Master's degree or PhD in a quantitative field such as Mathematics, Statistics, Physics, Economics, or Computer Science.
• Proven experience in quantitative analysis within the financial services industry.
• Strong programming skills in languages such as Python, R, C++, or Java.
• Proficiency in statistical modeling and machine learning techniques.
• Solid understanding of financial markets, derivatives, and fixed income.
• Excellent analytical and problem-solving abilities.
• Strong communication and presentation skills.

• Develop, implement, and maintain quantitative models for pricing, risk management, and hedging.
• Conduct in-depth statistical analysis of market data to identify trends and opportunities.
• Perform model validation, back-testing, and sensitivity analysis.
• Collaborate with front-office teams to understand their quantitative needs and provide solutions.
• Communicate complex analytical findings clearly and concisely to both technical and non-technical audiences.
• Stay abreast of the latest advancements in quantitative finance and technology.

• Master's or PhD in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field.
• Proven experience in quantitative finance, preferably in areas like derivatives pricing, risk management, or algorithmic trading.
• Proficiency in programming languages such as Python, C++, or R.
• Strong understanding of financial markets and instruments.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Ability to work independently and as part of a remote team.

• Develop, test, and implement sophisticated quantitative models for pricing complex financial instruments, including derivatives.
• Design and refine algorithms for algorithmic trading strategies and portfolio optimization.
• Conduct rigorous statistical analysis of market data to identify trends, patterns, and potential trading opportunities.
• Perform risk analysis, including VaR (Value at Risk) calculations, scenario analysis, and stress testing for trading portfolios.
• Collaborate closely with traders, portfolio managers, and IT teams to integrate models into production systems.
• Validate the performance of existing models and perform regular model reviews to ensure accuracy and relevance.
• Develop and maintain high-quality code in languages such as Python, C++, or R for model implementation and back-testing.
• Contribute to the development of new financial products and strategies.
• Ensure compliance with regulatory requirements and internal risk management policies.
• Document models, methodologies, and results clearly and comprehensively.
• Stay updated on the latest advancements in financial engineering, quantitative finance, and machine learning.
• Assist in the development and maintenance of risk reporting tools and dashboards.

• Master's degree or PhD in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field.
• Proven experience (3+ years) in a quantitative role within investment banking, asset management, hedge funds, or a similar financial services environment.
• Strong understanding of financial markets, financial instruments, and derivatives pricing.
• Proficiency in programming languages such as Python, C++, R, and SQL.
• Expertise in statistical modeling, time series analysis, econometrics, and machine learning techniques.
• Experience with numerical methods and simulation techniques (e.g., Monte Carlo).
• Excellent analytical, problem-solving, and critical thinking skills.
• Ability to communicate complex quantitative concepts to non-technical stakeholders.
• Strong attention to detail and a commitment to producing accurate and reliable results.
• Familiarity with financial databases (e.g., Bloomberg, Refinitiv) is a plus.
• Knowledge of regulatory frameworks like Basel III or MiFID II is advantageous.

• Develop, test, and implement quantitative models for pricing, risk management, and trading across various asset classes.
• Conduct in-depth statistical analysis of market data to identify trends, patterns, and potential trading opportunities.
• Design and execute backtesting strategies to validate model performance and robustness.
• Collaborate with traders and portfolio managers to understand their needs and translate them into quantitative solutions.
• Implement and optimize algorithms for real-time trading systems.
• Perform stress testing and scenario analysis to assess the impact of market events on portfolios.
• Contribute to the firm’s regulatory compliance efforts by providing data and analytical support.
• Stay abreast of the latest academic research and industry developments in quantitative finance.
• Prepare detailed reports and presentations on model performance, risk exposures, and market insights.

• Master's or Ph.D. in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Financial Engineering.
• Proven experience in quantitative analysis within the financial services industry.
• Strong programming skills in languages like Python, C++, R, or Java.
• Expertise in financial modeling, stochastic calculus, and statistical methods.
• Familiarity with financial derivatives and fixed income products.
• Excellent analytical, problem-solving, and critical thinking skills.
• Ability to work effectively in a high-pressure, fast-paced trading environment.
• Strong communication and presentation skills, with the ability to explain complex concepts clearly.

Senior Quantitative Analyst

Up to £130,000

London (Fully Onsite)

Please note: This role cannot provide sponsorship

Company:

Join a world-class global investment management firm that specialises in sports trading, spanning football, soccer, cricket, and major US sports like the NBA. As part of their elite trading team, you’ll harness advanced statistical techniques and machine learning to build predictive models that shape their trading strategies.

In this role, you’ll drive revenue growth and develop mathematical models to predict the outcomes of sports events.

Responsibilities:

• Utilise advanced statistical techniques and machine learning to build predictive models that shape our trading strategies
• Develop predictive models for sports outcomes using advanced mathematical and statistical techniques.
• Analyse real-world sports data to uncover patterns and generate insights that inform trading strategies.
• Implement and optimise numerical methods to support robust, scalable model performance in live environments.
• Collaborate closely with fellow researchers and developers in a fast-paced, science-driven team environment.
• Continuously innovate and improve modelling approaches to stay competitive in dynamic and data-rich sports markets.

Requirements:

• MSc, PhD Degree in Mathematics
• Have 5+ years of relevant industry experience.
• Strong coding skills in Python and SQL
• Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment.
• Strong background in mathematics, statistics, or a related quantitative field
• Experience in developing mathematical models to predict real-world outcomes
• Proficiency in numerical implementation and computational methods