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FinCrime Data Analyst Lead

Barclays · Posted Nov 5

Banking, credit card, corporate, investment banking, and wealth management services

Pune, IndiaFull-timeOnsiteLead/Staff10+ years₹40.0L–₹60.0L yearly57 applicants
BankingFinancial ServicesInvestment BankingCredit CardsWealth ManagementPublic Company
Full time

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About the role

The Financial Crime Agile Testing team at Barclays oversees risk-based testing of financial crime processes and controls. The role leads data analytics for testing reviews, defining analytical objectives, hypotheses and testing plans and providing quality control over SQL, Python and SAS scripts and outputs. It translates data-led findings into insight for stakeholders and supports assessment of the operational effectiveness of financial crime controls.

What you will do

  • Oversee data analytics work performed within the Financial Crime Agile Testing team, including defining the data analytics testing strategy required for individual reviews.
  • Translate review triggers into executable objectives, hypotheses and data analytics testing plans, providing data-led input to scoping decisions in collaboration with non-Data Analytics review colleagues.
  • Provide leadership and technical oversight for the development of analytical test objectives, methodologies and scripts using SQL, Python and SAS; review and approve analytical work to support robust and reproducible testing outcomes.
  • Identify and agree data needs and analytical design with the Agile Testing Lead during review planning and test-plan development.
  • Coordinate delivery of analytics with the Agile Testing Lead during testing execution, while Data Analytics Specialists and Analysts design scripts, source data and perform analysis.
  • Perform quality-control reviews of analytical scripts, including SQL, SAS and Python, designed by Data Analytics Specialists and/or Data Analytics Analysts, challenging logic, assumptions, data quality, caveats and the sufficiency of analytical evidence.
  • Review analytical outputs and workpaper content to support clear, accurate and reproducible documentation of the testing performed, evidence obtained and conclusions supported by the analysis.
  • Interpret and communicate findings and observations arising from data analytics testing to external stakeholders and provide analytical insight and draft input to review conclusions and reporting.
  • Act as the escalation route for Data Analytics Specialists and Analysts, addressing analytical judgement matters within authority and escalating material risk, scope, timeline or stakeholder issues where appropriate.
  • Work alongside the Agile Testing Lead as part of stage-gate oversight and peer cross-review, preserving independent challenge and clear accountability between Testing and Data Analytics roles.
  • Support the ongoing review and improvement of data analytics requirements within the Agile Testing methodology and contribute to efficient, risk-based and hypothesis-led review delivery.
  • Maintain independence and objectivity, ensure timely escalation, secure evidence retention, data-privacy compliance and high-quality documentation across data analytics work.
  • Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement
  • Designing and building data pipelines to automate data movement and processing.
  • Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
  • Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
  • Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.

Skills used in this role

What the employer is looking for

  • Strong experience leading data analytics work in Financial Crime, Compliance, Risk, Audit, Assurance or another control-testing environment.
  • Strong SQL and Python capability, including the ability to review and challenge analytical scripts, logic, assumptions and outputs developed by others.
  • Experience translating risk or review triggers into analytical objectives, hypotheses, testing plans, data requirements and executable analytical approaches.
  • Strong understanding of Financial Crime processes, risks and controls across relevant domains such as AML, Sanctions, Customer Due Diligence/KYC, Fraud or Transaction Monitoring.
  • Experience applying data analytics to assess control effectiveness using full-population or targeted testing approaches.
  • Strong technical assurance, critical-thinking and problem-solving skills, including the ability to identify data-quality issues, anomalies, control weaknesses, caveats and limitations.
  • Experience reviewing analytical evidence and workpapers to determine whether testing outputs sufficiently support observations and conclusions.
  • Excellent written and verbal communication skills, with the ability to explain analytical findings clearly to technical and non-technical stakeholders.
  • Strong stakeholder engagement, collaboration and constructive-challenge skills, with the ability to exercise independent judgement and escalate appropriately.
  • Ability to coordinate analytical delivery, provide technical guidance and act as an escalation point for Data Analytics Specialists and Analysts.

Preferred qualifications

  • Experience contributing to Financial Crime assurance or Agile Testing methodology and improving analytical testing standards or ways of working.
  • Experience with SAS, data visualisation tools such as Tableau, statistical analysis, data mining or AI-enabled analytics.
  • Experience developing reusable analytical assets or automated testing approaches that improve testing efficiency, consistency or coverage.
  • Knowledge of advanced statistical or machine-learning techniques used to identify patterns, trends and relationships in data.
  • Working knowledge of AWS cloud services, LLM architectures, including responsible AI principles and appropriate solution validation.

Benefits and support

  • Compensation and benefits are detailed in the job posting

About Barclays

Barclays logo

Barclays

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Barclays is a British multinational universal bank that provides consumer, corporate, and investment banking, as well as wealth management services. Tracing its origins back to 1690 in London, the institution operates globally to serve millions of retail and institutional clients. The bank leverages cutting-edge technology and digital platforms to drive operational efficiency across its international network.

Industry
Banking
Company size
93000+ employees
Founded
1690
Location
London, United Kingdom
Funding stage
Public Company

Leadership

CV
C.S. Venkatakrishnan

Group Chief Executive

AC
Anna Cross

Group Finance Director

AC
Alistair Currie

Group Chief Operating Officer

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