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.