Role: Data Analyst - Min - 6 years of Exp
Key Responsibilities:
1. Strategic Leadership & Roadmap Development
- Define the Vision: Design and execute the long-term data analytics strategy, for proactive Continuous Monitoring.
- Methodology Evolution: Lead the transition toward full-population testing by embedding analytics into the risk assessment phase.
- Governance Framework: Strengthen data governance framework to ensure the integrity, security, and accuracy of data used in audit reporting, ensuring all workflows are documented for regulatory reliance.
2. Advanced Analytics & Tech Stack (Python, SQL, Power BI)
- Advanced Modeling (Python): Oversee the development of complex models using Python or R. Utilize predictive analytics, statistical sampling, and machine learning algorithms to anticipate emerging risks rather than just reporting on past events.
- Data Extraction & Manipulation (SQL): leverage advanced SQL scripting to query enterprise data warehouses directly.
- Visualization & Storytelling (Power BI): Architect dynamic executive dashboards using Power BI that translate complex datasets into intuitive visual stories, allowing stakeholders to self-serve risk insights.
- Fraud Detection: Architect sophisticated fraud detection scenarios and behavioral analysis models to identify anomalies across financial and operational datasets.
3. Stakeholder Management & Business Impact
- Translating Data to Value: Act as the bridge between technical data teams and business stakeholders. You must articulate complex findings into clear, actionable business insights for the Audit Committee.
- Business Acumen: Apply deep business knowledge to analytics. You must understand how the business generates revenue and where operational risks lie to ensure models are commercially relevant, not just theoretically correct.
- Cross-Functional Collaboration: Partner with internal teams to leverage existing data lakes and align on architecture.
4. Team Leadership & Quality Assurance
- Mentorship: Manage and mentor a team of data analysts and auditors. Foster their technical growth in SQL querying, Python scripting, and Power BI dashboarding.
- Quality Control: Ensure all analytical deliverables meet rigorous documentation standards. Validate code logic and query integrity to ensure results are accurate and suitable for external audit reliance.
