FinCrime Agile Testing Data Analyst

Job Description

Purpose of the role

To provide data-led expert oversight and check and challenge on business and compliance matters to evidence that the organisation is operating in a compliance with Barclays legal, regulatory and ethical responsibilities. 

Accountabilities

• Identification and assessment of compliance risks through thorough reviews of business activities, changes, processes, testing and systems to.
• Identification and investigation of potential market abuse, including but not limited to, Insider Dealing, Unlawful Disclosure, Market Manipulation or Anti-Competitive Conduct.
• Conduct investigation of compliance risk events or breaches. Oversight and check and challenge of corrective actions and preventative measures to avoid future occurrences.
• Implementation of compliance policies and procedures in line with regulatory requirements and ensuring that the bank’s internal policies are aligned with international standards, including jurisdictional requirements.
• Collaboration with 1LOD, other relevant Compliance teams and legal, and relevant risk management functions to facilitate a comprehensive approach to compliance and risk management.
• Identification, investigation and oversight of potential money laundering, terrorist financing or other financial crime.

Analyst Expectations

• To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in their assigned area of expertise
• Thorough understanding of the underlying principles and concepts within the area of expertise
• They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate.
• Will have an impact on the work of related teams within the area.
• Partner with other functions and business areas.
• Takes responsibility for end results of a team’s operational processing and activities.
• Escalate breaches of policies / procedure appropriately.
• Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
• Advise and influence decision making within own area of expertise.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
• Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Make evaluative judgements based on the analysis of factual information, paying attention to detail.
• Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
• Guide and persuade team members and communicate complex / sensitive information.
• Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us as a FinCrime Agile Testing Data Analyst at Barclays, where you'll help shape the future of Financial Crime risk management through data-driven testing, analytics, and insight generation. You will leverage data, technology, and analytical techniques to assess the effectiveness of Financial Crime controls, identify emerging risks, and support agile testing activities across key Financial Crime domains. Working closely with Compliance, Operations, Technology, and Risk stakeholders, you will deliver actionable insights that strengthen Barclays' control environment and support regulatory compliance. The role forms part of Barclays’ evolving agile testing capability within Financial Crime, focused on providing timely, risk-based assurance through the intelligent use of data and analytics.

You may be assessed on the key critical skills relevant for success in the role, such as experience with data analytics, SQL, SAS, Python, AI, control testing along with domain knowledge of Financial Crime processes, as well as job-specific skillsets

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities

• Perform data-driven testing and analytics to assess the effectiveness of Financial Crime controls and processes.
• Develop and execute analytical test scripts using DA programming languages like SQL, Python & SAS to identify potential control gaps, anomalies, and emerging risks.
• Analyse large datasets from multiple sources including performing data cleaning, wrangling and transformation to support agile testing reviews and thematic investigations.
• Design and create interactive dashboards, visualisations, and reports that provide meaningful management insights and support decision-making.
• Partner with Compliance, Operations, Technology, and Risk stakeholders to understand business processes and testing requirements.
• Provide guidance to stakeholders on the remediation of control weaknesses and outcome risks by participating in discussions and using technical knowledge for effective remediation. Propose action plans to address root causes of issues identified in testing.
• Support the development of automated testing approaches and reusable analytical solutions.
• Document testing methodologies, analytical logic, findings, and recommendations to a high standard.
• Contribute to continuous improvement initiatives by identifying opportunities to leverage analytics, automation, and emerging technologies to improve testing efficiency and insight generation

Essential Qualifications:

• Experience in Data Analytics, Financial Crime, Compliance, Risk, Audit, or a related field.
• Strong SQL, Python and SAS skills with experience analysing large and complex datasets from Financial Crime Disciplines like KYC Onboarding, AML, Transaction Monitoring, Sanctions etc.
• Knowledge of statistical analysis, data mining, NLP, and AI-enabled analytics and experience using data visualization tools such as Tableau, or equivalent.
• Experience performing data-driven control testing, quality assurance, risk assessments, or investigative analysis
• Understanding of Financial Crime domains, including AML, Sanctions, Customer Due Diligence (CDD/KYC), Fraud, or Transaction Monitoring.
• Strong analytical and problem-solving skills with the ability to identify trends, anomalies, and control weaknesses.
• Excellent interpersonal and communication skills, with the ability to articulate complex analytical findings in a clear, concise, and meaningful manner to both technical and non-technical audiences.

Desirable skillsets:

• Stakeholder management skills with the ability to build effective working relationships across Compliance, Financial Crime Operations, Technology, Data, Risk and Business teams.
• Knowledge of advanced statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Ability to develop and implement predictive models to forecast future outcomes and identify potential risks and opportunities.
• Working knowledge of AWS cloud services, Amazon Bedrock, and LLM architectures, with an understanding of AI/GenAI solution design, retrieval-augmented generation (RAG), model orchestration, prompt engineering, and responsible AI principles.

Job Profile Summary

Join us as a FinCrime Agile Testing Data Analyst at Barclays, where you'll help shape the future of Financial Crime risk management through data-driven testing, analytics, and insight generation. You will leverage data, technology, and analytical techniques to assess the effectiveness of Financial Crime controls, identify emerging risks, and support agile testing activities across key Financial Crime domains. Working closely with Compliance, Operations, Technology, and Risk stakeholders, you will deliver actionable insights that strengthen Barclays' control environment and support regulatory compliance. The role forms part of Barclays’ evolving agile testing capability within Financial Crime, focused on providing timely, risk-based assurance through the intelligent use of data and analytics.

You may be assessed on the key critical skills relevant for success in the role, such as experience with data analytics, SQL, SAS, Python, AI, control testing along with domain knowledge of Financial Crime processes, as well as job-specific skillsets

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities

• Perform data-driven testing and analytics to assess the effectiveness of Financial Crime controls and processes.
• Develop and execute analytical test scripts using DA programming languages like SQL, Python & SAS to identify potential control gaps, anomalies, and emerging risks.
• Analyse large datasets from multiple sources including performing data cleaning, wrangling and transformation to support agile testing reviews and thematic investigations.
• Design and create interactive dashboards, visualisations, and reports that provide meaningful management insights and support decision-making.
• Partner with Compliance, Operations, Technology, and Risk stakeholders to understand business processes and testing requirements.
• Provide guidance to stakeholders on the remediation of control weaknesses and outcome risks by participating in discussions and using technical knowledge for effective remediation. Propose action plans to address root causes of issues identified in testing.
• Support the development of automated testing approaches and reusable analytical solutions.
• Document testing methodologies, analytical logic, findings, and recommendations to a high standard.
• Contribute to continuous improvement initiatives by identifying opportunities to leverage analytics, automation, and emerging technologies to improve testing efficiency and insight generation

Basic/ Essential Qualifications:

• Experience in Data Analytics, Financial Crime, Compliance, Risk, Audit, or a related field.
• Strong SQL, Python and SAS skills with experience analysing large and complex datasets from Financial Crime Disciplines like KYC Onboarding, AML, Transaction Monitoring, Sanctions etc.
• Knowledge of statistical analysis, data mining, NLP, and AI-enabled analytics and experience using data visualization tools such as Tableau, or equivalent.
• Experience performing data-driven control testing, quality assurance, risk assessments, or investigative analysis
• Understanding of Financial Crime domains, including AML, Sanctions, Customer Due Diligence (CDD/KYC), Fraud, or Transaction Monitoring.
• Strong analytical and problem-solving skills with the ability to identify trends, anomalies, and control weaknesses.
• Excellent interpersonal and communication skills, with the ability to articulate complex analytical findings in a clear, concise, and meaningful manner to both technical and non-technical audiences.

Desirable skillsets/ good to have:

• Stakeholder management skills with the ability to build effective working relationships across Compliance, Financial Crime Operations, Technology, Data, Risk and Business teams.
• Knowledge of advanced statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Ability to develop and implement predictive models to forecast future outcomes and identify potential risks and opportunities.
• Working knowledge of AWS cloud services, Amazon Bedrock, and LLM architectures, with an understanding of AI/GenAI solution design, retrieval-augmented generation (RAG), model orchestration, prompt engineering, and responsible AI principles.

Job Profile Summary

Join us as a FinCrime Agile Testing Data Analyst at Barclays, where you'll help shape the future of Financial Crime risk management through data-driven testing, analytics, and insight generation. You will leverage data, technology, and analytical techniques to assess the effectiveness of Financial Crime controls, identify emerging risks, and support agile testing activities across key Financial Crime domains. Working closely with Compliance, Operations, Technology, and Risk stakeholders, you will deliver actionable insights that strengthen Barclays' control environment and support regulatory compliance. The role forms part of Barclays’ evolving agile testing capability within Financial Crime, focused on providing timely, risk-based assurance through the intelligent use of data and analytics.

You may be assessed on the key critical skills relevant for success in the role, such as experience with data analytics, SQL, SAS, Python, AI, control testing along with domain knowledge of Financial Crime processes, as well as job-specific skillsets

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities

• Perform data-driven testing and analytics to assess the effectiveness of Financial Crime controls and processes.
• Develop and execute analytical test scripts using DA programming languages like SQL, Python & SAS to identify potential control gaps, anomalies, and emerging risks.
• Analyse large datasets from multiple sources including performing data cleaning, wrangling and transformation to support agile testing reviews and thematic investigations.
• Design and create interactive dashboards, visualisations, and reports that provide meaningful management insights and support decision-making.
• Partner with Compliance, Operations, Technology, and Risk stakeholders to understand business processes and testing requirements.
• Provide guidance to stakeholders on the remediation of control weaknesses and outcome risks by participating in discussions and using technical knowledge for effective remediation. Propose action plans to address root causes of issues identified in testing.
• Support the development of automated testing approaches and reusable analytical solutions.
• Document testing methodologies, analytical logic, findings, and recommendations to a high standard.
• Contribute to continuous improvement initiatives by identifying opportunities to leverage analytics, automation, and emerging technologies to improve testing efficiency and insight generation

Basic/ Essential Qualifications:

• Experience in Data Analytics, Financial Crime, Compliance, Risk, Audit, or a related field.
• Strong SQL, Python and SAS skills with experience analysing large and complex datasets from Financial Crime Disciplines like KYC Onboarding, AML, Transaction Monitoring, Sanctions etc.
• Knowledge of statistical analysis, data mining, NLP, and AI-enabled analytics and experience using data visualization tools such as Tableau, or equivalent.
• Experience performing data-driven control testing, quality assurance, risk assessments, or investigative analysis
• Understanding of Financial Crime domains, including AML, Sanctions, Customer Due Diligence (CDD/KYC), Fraud, or Transaction Monitoring.
• Strong analytical and problem-solving skills with the ability to identify trends, anomalies, and control weaknesses.
• Excellent interpersonal and communication skills, with the ability to articulate complex analytical findings in a clear, concise, and meaningful manner to both technical and non-technical audiences.

Desirable skillsets/ good to have:

• Stakeholder management skills with the ability to build effective working relationships across Compliance, Financial Crime Operations, Technology, Data, Risk and Business teams.
• Knowledge of advanced statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Ability to develop and implement predictive models to forecast future outcomes and identify potential risks and opportunities.
• Working knowledge of AWS cloud services, Amazon Bedrock, and LLM architectures, with an understanding of AI/GenAI solution design, retrieval-augmented generation (RAG), model orchestration, prompt engineering, and responsible AI principles.

This role will be based out of Pune