922 Securities Analyst jobs in the United Kingdom

• Develop, validate, and implement complex quantitative models for pricing, risk management, and trading strategies across various asset classes (e.g., equities, fixed income, derivatives).
• Analyze large datasets to identify market trends, assess risk exposures, and support investment decisions.
• Collaborate with traders, portfolio managers, and risk officers to understand their analytical needs and provide tailored solutions.
• Design and execute back-testing and scenario analysis for developed models.
• Ensure models are compliant with regulatory requirements and internal policies.
• Contribute to the technological infrastructure supporting quantitative research and development.
• Develop and maintain clear and concise documentation for all models and methodologies.
• Present complex quantitative findings to both technical and non-technical stakeholders.
• Identify opportunities for model improvement and innovation.
• Mentor junior quantitative analysts and contribute to team development.
• Stay abreast of industry best practices, emerging financial instruments, and regulatory changes.
• Work closely with IT teams to ensure efficient implementation and deployment of models.

• Master's degree or PhD in a quantitative field such as Mathematics, Physics, Statistics, Economics, Computer Science, or Financial Engineering.
• Minimum of 5 years of experience in a quantitative analyst role within investment banking, asset management, or a hedge fund.
• Strong expertise in financial modeling, including stochastic calculus, time series analysis, and derivative pricing.
• Proficiency in programming languages such as Python, C++, R, or MATLAB.
• Experience with financial databases and data manipulation tools (e.g., SQL).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong understanding of financial markets, trading strategies, and risk management principles.
• Ability to communicate complex technical concepts effectively to diverse audiences.
• Experience with risk management frameworks (e.g., VaR, CVA, XVA) is a plus.
• Familiarity with machine learning techniques applied to finance is advantageous.
• Ability to work effectively in a fast-paced, team-oriented environment.

• Develop, test, and deploy advanced quantitative models for pricing, risk management, and hedging of financial derivatives.
• Lead a team of quantitative analysts, providing technical guidance and mentorship.
• Collaborate with traders, portfolio managers, and risk officers to understand their modeling needs.
• Perform rigorous back-testing and validation of model performance against market data.
• Identify and research new mathematical approaches and statistical techniques for financial modeling.
• Contribute to the design and implementation of robust data infrastructure for quantitative analysis.
• Communicate complex modeling concepts and results clearly to diverse stakeholders.
• Stay updated with regulatory changes and their impact on financial modeling requirements.
• Ensure compliance with internal policies and industry best practices.
• Drive innovation in quantitative research and model development.

• Master's or PhD in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, or Financial Engineering.
• Minimum of 7 years of experience in quantitative finance, with at least 2 years in a lead or senior role.
• Strong expertise in stochastic calculus, time series analysis, and numerical methods.
• Proficiency in programming languages commonly used in quant finance, such as Python (NumPy, SciPy, Pandas), C++, or R.
• Experience with large datasets and database technologies (e.g., SQL).
• Deep understanding of various financial markets (equities, fixed income, derivatives).
• Proven ability to lead projects and mentor junior team members.
• Excellent problem-solving and analytical skills.
• Strong communication and presentation abilities.
• Demonstrated success in developing and deploying production-level quantitative models.
• Must be able to work effectively in a fully remote setting.

• Design, develop, and implement cutting-edge quantitative models for pricing derivatives, assessing risk, and optimizing trading strategies.
• Perform rigorous back-testing and validation of models to ensure accuracy, robustness, and compliance with regulatory requirements.
• Collaborate closely with traders, portfolio managers, risk officers, and IT teams to understand business needs and translate them into quantitative solutions.
• Analyze large datasets to identify market trends, generate insights, and inform model enhancements.
• Contribute to the development and enhancement of the firm's risk management framework through sophisticated modeling techniques.
• Research and evaluate new quantitative methodologies and technologies to improve modeling capabilities.
• Document model specifications, assumptions, methodologies, and limitations thoroughly.
• Present complex quantitative concepts and findings clearly and concisely to both technical and non-technical audiences.
• Mentor junior quantitative analysts and contribute to the team's overall technical expertise.
• Ensure adherence to all internal policies and external regulations governing financial modeling and risk management.

• Master's degree or PhD in a quantitative field such as Financial Engineering, Mathematics, Statistics, Physics, or Computer Science.
• Minimum of 5 years of experience in a quantitative analysis role within the financial services industry.
• Strong proficiency in programming languages commonly used in quantitative finance, such as Python (NumPy, SciPy, Pandas), C++, or R.
• Extensive experience with financial modeling techniques, including Monte Carlo simulations, time series analysis, stochastic calculus, and econometrics.
• Deep understanding of financial derivatives, fixed income, equities, and risk management principles.
• Experience with data manipulation and database technologies (e.g., SQL).
• Excellent analytical, problem-solving, and critical thinking skills.
• Effective communication and presentation skills, with the ability to articulate complex ideas.
• Ability to work independently and collaboratively in a fast-paced, team-oriented environment.
• Familiarity with regulatory frameworks such as Basel III and Solvency II is a plus.
• Experience working in a hybrid office setup, balancing remote collaboration with in-person meetings.

• Develop, test, and implement complex mathematical and statistical models for financial risk assessment, asset valuation, and portfolio optimization.
• Design and build pricing models for various financial instruments, including derivatives and structured products.
• Conduct rigorous backtesting and validation of models to ensure accuracy and robustness.
• Collaborate with trading desks, portfolio managers, and risk management teams to understand their analytical needs and provide tailored solutions.
• Translate business requirements into technical specifications for model development.
• Write clean, efficient, and well-documented code in languages such as Python, R, or C++.
• Analyze large datasets to identify trends, patterns, and insights relevant to financial markets.
• Stay current with industry best practices, regulatory changes, and emerging quantitative techniques.
• Prepare comprehensive documentation of models, methodologies, and results.
• Communicate complex quantitative concepts clearly and concisely to both technical and non-technical audiences.
• Contribute to the development of trading strategies and risk management frameworks.
• Mentor junior quantitative analysts and contribute to the team's knowledge sharing.

• Master's or PhD in a quantitative field such as Mathematics, Statistics, Physics, Economics, or Computer Science.
• Minimum of 5 years of relevant experience in quantitative analysis, financial modeling, or risk management within the financial services industry.
• Expertise in developing and implementing models for pricing, risk, or trading.
• Proficiency in programming languages such as Python, R, C++, or MATLAB.
• Strong understanding of financial markets, instruments, and derivatives.
• Excellent analytical, problem-solving, and statistical modeling skills.
• Ability to work effectively in a hybrid work environment, balancing remote and in-office responsibilities.
• Strong written and verbal communication skills.
• Experience with big data technologies and machine learning techniques is a plus.

• Develop, validate, and implement sophisticated quantitative models for financial markets.
• Conduct in-depth statistical analysis and data mining of large financial datasets.
• Design and test trading algorithms and investment strategies.
• Perform risk analysis and develop risk management models.
• Collaborate with portfolio managers and traders to provide quantitative insights.
• Optimize existing models for performance and accuracy.
• Stay abreast of the latest developments in quantitative finance and econometrics.
• Write clean, efficient, and well-documented code in languages like Python, R, or C++.
• Present complex quantitative findings to stakeholders in a clear and understandable manner.

• Master's or Ph.D. in a quantitative field such as Finance, Mathematics, Statistics, Physics, or Computer Science.
• Minimum of 7 years of experience in quantitative analysis within the financial services industry.
• Proven expertise in financial modeling, time-series analysis, and statistical techniques.
• Strong programming skills in Python, R, C++, or similar languages.
• Experience with financial data vendors (e.g., Bloomberg, Refinitiv) and databases.
• Knowledge of derivatives pricing, risk management, and portfolio optimization.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation abilities, effective in a remote team environment.
• Ability to work independently and manage multiple projects simultaneously.

• Develop, validate, and deploy advanced statistical and machine learning models for financial applications.
• Conduct comprehensive data analysis to identify trends, risks, and opportunities in financial markets.
• Build predictive models for forecasting, risk management, fraud detection, and portfolio optimization.
• Collaborate with quantitative analysts, traders, and risk managers to define modeling requirements.
• Ensure model accuracy, robustness, and compliance with regulatory standards.
• Communicate complex analytical findings and recommendations to senior leadership.
• Stay abreast of the latest advancements in data science, machine learning, and financial modeling.

• Master's degree or Ph.D. in Finance, Economics, Statistics, Mathematics, Computer Science, or a related quantitative field.
• 5+ years of experience in data science, with a strong focus on financial modeling and analysis.
• Proficiency in Python or R, and extensive experience with data manipulation and modeling libraries.
• Strong SQL skills and experience with relational databases.
• Deep understanding of financial markets, instruments, and risk management principles.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent analytical, problem-solving, and communication skills.

The Company:

Our client is a highly successful and expandingInvestment Management firm, widely recognised with an excellent reputation based in London.

The Role:

TheSenior SecuritiesDataAnalyst role sits within the Securities & Data Team - this is part of the Custody & Execution Services business area of the Investment Management firm.

The Senior Securities Data Analyst will primarily be responsible f.

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• Design, develop, and implement sophisticated data models using machine learning and statistical techniques to identify, measure, and manage financial risks.
• Analyze large, complex datasets to uncover trends, patterns, and insights related to market risk, credit risk, and operational risk.
• Collaborate with risk managers, traders, and other stakeholders to define risk modeling requirements and objectives.
• Validate and back-test models to ensure their accuracy, reliability, and compliance with regulatory standards.
• Develop and maintain production-ready code for model deployment and monitoring, using languages such as Python or R.
• Conduct scenario analysis and stress testing to evaluate the potential impact of adverse market conditions.
• Contribute to the continuous improvement of risk management frameworks and methodologies.
• Prepare clear and concise documentation and present findings and recommendations to senior management and regulatory bodies.
• Stay abreast of the latest advancements in data science, machine learning, and financial risk management.
• Ensure all modeling activities comply with internal policies and external regulatory requirements.

• Master's or Ph.D. in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or Economics.
• Minimum of 5 years of experience as a Data Scientist or in a similar role within the financial services industry, with a focus on risk modeling.
• Strong proficiency in Python or R, including experience with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of financial markets, various types of financial risk, and regulatory frameworks (e.g., Basel III).
• Experience with database technologies (SQL, NoSQL) and big data platforms.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts to a diverse audience.
• Ability to work effectively both independently and collaboratively within a team environment.