FinCrime Agile Testing Data Analyst

Overview

Provide data-driven testing, analytics and insight generation to assess the effectiveness of Financial Crime controls, identify emerging risks, and support agile testing activities across key Financial Crime domains.

What you'll do

• Perform data-driven testing and analytics to assess the effectiveness of Financial Crime controls and processes.
• Develop and execute analytical test scripts using SQL, Python and SAS to identify potential control gaps, anomalies, and emerging risks.
• Analyse large datasets from multiple sources, including 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 remediation of control weaknesses and outcome risks.
• 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 by identifying opportunities to leverage analytics, automation, and emerging technologies.

What you'll need

• 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 such as KYC Onboarding, AML, Transaction Monitoring, Sanctions etc.
• Knowledge of statistical analysis, data mining, NLP, and AI-enabled analytics.
• Experience using data visualisation 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, able to articulate complex analytical findings clearly to technical and non-technical audiences.

Nice 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 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 understanding of AI/GenAI solution design, retrieval-augmented generation (RAG), model orchestration, prompt engineering, and responsible AI principles.

Details

• Based out of Pune.