FinCrime Data Analyst Lead

Overview

Lead the data analytics work supporting Financial Crime Agile Testing reviews, defining the analytical testing approach, hypotheses and test plans, and providing quality control over analytical scripts and outputs.

What you'll do

• Oversee data analytics work performed within the Financial Crime Agile Testing team, including defining the data analytics testing strategy for individual reviews.
• Translate review triggers into executable objectives, hypotheses and data analytics testing plans, providing data-led input to scoping decisions.
• 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.
• 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.
• Perform quality-control reviews of analytical scripts (SQL, SAS and Python), 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 testing performed, evidence obtained and conclusions supported.
• Interpret and communicate findings and observations from data analytics testing to external stakeholders and provide 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.
• Work alongside the Agile Testing Lead as part of stage-gate oversight and peer cross-review, preserving independent challenge.
• Support the ongoing review and improvement of data analytics requirements within the Agile Testing methodology.
• Maintain independence and objectivity, ensure timely escalation, secure evidence retention, data-privacy compliance and high-quality documentation across data analytics work.

What you'll need

• 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 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 identifying 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.

Nice to have

• 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.

Details

• Location: Pune, Gera Commerzone SEZ.