Position Overview
We are seeking a highly experienced Data Analyst to support our Assurance, Compliance, and Risk functions through advanced analytics, automation, and AI-driven insights. This is a senior, hands-on technical role requiring strong expertise in Python, SQL, Power BI, and Azure cloud. The ideal candidate has deep experience working with financial services data and can design, build, and operationalize analytics solutions that enhance risk monitoring, regulatory compliance, and assurance capabilities.
Key Responsibilities
Data Analytics for Assurance & Compliance
- Translate business, audit, and compliance requirements into robust data models and analytical solutions.
- Lead data extraction, cleaning, transformation, and validation across complex financial systems.
- Perform deep exploratory analytics to identify trends, anomalies, control gaps, and risk indicators.
- Build automated datasets and pipelines for continuous monitoring and compliance analytics.
Reporting, Dashboards & Visualization
- Design and deliver advanced Power BI dashboards using strong DAX, modelling, and visualization techniques.
- Present insights clearly to senior stakeholders and influence data-driven decision making.
- Develop continuous monitoring dashboards for risk, compliance, and control effectiveness.
Python & SQL Development
- Build sophisticated Python scripts for ETL, automation, statistical modelling, ML, and NLP.
- Develop optimized SQL queries for large, complex, structured and semi-structured datasets.
- Create reusable code frameworks, templates, and analytics utilities to standardize processes.
Cloud & Data Platform Integration
- Work primarily within Azure (Data Lake, Synapse, Databricks, Azure SQL, Azure ML).
- Integrate analytics solutions with enterprise cloud data platforms and pipelines.
- Support multi-cloud data work (AWS or GCP) when required.
AI, Machine Learning & Advanced Techniques
- Develop ML models for anomaly detection, clustering, classification, and predictive analytics.
- Apply NLP techniques to analyze text-based documents such as policies, customer interactions, logs, and transactional narratives.
- Build prototypes and production-ready AI models to enhance assurance and compliance functions.
- Translate AI/ML outputs into usable insights via dashboards and monitoring tools.
- Ensure responsible and explainable AI practices.
Qualifications
Education & Experience
- Bachelor's degree in Data Analytics, Computer Science, Information Systems, Statistics, Finance, or related field.
- 712 years of experience as a Data Analyst, Data Scientist, or Analytics Specialist, preferably in financial services.
- Experience leading analytics initiatives and working with senior stakeholders.
Technical Skills
- Advanced expertise in Python for data processing, automation, ML, and NLP.
- Strong SQL experience across multiple database platforms.
- Expert-level Power BI skills (DAX, semantic modelling, data storytelling).
- Hands-on experience with Azure cloud technologies.
- Strong understanding of AI/ML concepts and practical implementation experience.
Domain Skills
- Knowledge of compliance requirements, risk frameworks, and assurance methodologies in financial institutions.
- Familiarity with banking operations, financial products, risk indicators, and regulatory reporting.
Soft Skills
- Strong analytical mindset with the ability to solve complex problems.
- Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- High attention to detail and a commitment to data accuracy.
- Ability to work independently and collaborate across functions.
- Comfortable leading initiatives and driving adoption of analytics solutions.
Preferred Certifications (Optional)
- Microsoft Azure Data Engineer / Azure Data Fundamentals
- Power BI Data Analyst Associate
- Certifications in AI/ML, Python, or cloud engineering
- Compliance, risk, or financial services certifications
What We Offer
- Opportunities to drive analytics and AI innovation within assurance and compliance functions.
- Exposure to enterprise cloud platforms and advanced data technologies.
- A collaborative environment focused on learning, innovation, and continuous improvement.
