jazzhr
Data Analyst - Senior Associate
Forensic Risk Alliance
London, GBR
Full-time
Senior · 3+ years experience
Onsite
Discovered 2 weeks ago
SQLSQL ServerPostgreSQLOracleDuckDBPython
Free
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SQLSQL ServerPostgreSQL
Key Skills for This Role
SQLSQL ServerPostgreSQLOracleDuckDBPython
Full Job Posting
- Design data workflows spanning data collection, ETL, analysis, visualisation, and delivery across structured and semi-structured datasets
- Apply advanced analytical techniques to identify patterns of fraud, corruption, misconduct, and financial crime
- Implement analytical workflows that are fully reproducible, deterministic, and auditable, ensuring that outputs can be independently validated and withstand scrutiny in regulatory and legal contexts
- Work with complex enterprise data (ERP systems, transactional data, communications, logs) to reconstruct events and generate evidence-based insights
- Develop scalable analytical solutions using modern data tools and programming languages
- Translate analytical outputs into clear, defensible insights for non-technical stakeholders including legal counsel, regulators, and senior executives
- Collaborate closely with investigators, forensic accountants, and legal teams on cross-border matters
- Maintain rigorous documentation of data sources, transformations, assumptions, and methodologies to establish clear audit trails and evidentiary integrity
- Contribute to the development of reusable tools, methodologies, and intellectual property within the practice
- SQL-based data platforms (e.g., SQL Server, PostgreSQL, Oracle, DuckDB)
- Python for data processing, statistical analysis, and automation
- Data visualisation tools (Power BI) for storytelling and reporting
- Professional development environments and tooling (e.g., version control systems such as Git, and modern IDEs such as VS Code) to support controlled, traceable, and reproducible analytical workflows
- Cloud platforms (primarily Microsoft Azure)
- Exposure to machine learning, network analytics, and entity resolution techniques
- 3+ years of professional experience working in data analytics or a related field
- Demonstrated proficiency in SQL and at least one programming language (Python preferred)
- Experience working with large, complex datasets and deriving actionable insights
- Strong academic background in a quantitative or analytical field (e.g., Computer Science, Engineering, Statistics, Mathematics, Economics, or similar)
- Experience developing analytics that are reproducible, traceable, and methodologically robust, particularly in environments subject to external scrutiny
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