Fraud Technical Data Analyst

Brightonparkbank

Northampton, United Kingdom
**
Sas and sql for data exploration
Etl, cdc, and data warehousing tooling
Designing and delivering data-driven solutions
** Brightonparkbank is seeking a Fraud Technical Data Analyst to leverage data-driven insights for fraud detection and prevention. The role involves analyzing large datasets, designing data pipelines, and collaborating with stakeholders to drive operational improvements and ensure data quality. **

Job Summary

  • Enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.
  • Join us as a Fraud Technical Data Analyst where you’ll play a critical role in designing and delivering data-driven solutions that support fraud detection, prevention, and reporting.
  • This technical role blends evaluative depth with strategic insight, enabling collaboration across fraud, data technology, and business teams to protect customers and the organisation from financial crime.

Matching Summary

Match Score: 75

** Brightonparkbank is seeking a Fraud Technical Data Analyst to leverage data-driven insights for fraud detection and prevention. The role involves analyzing large datasets, designing data pipelines, and collaborating with stakeholders to drive operational improvements and ensure data quality. **

Skills & Requirements

Must-have

  • SAS and SQL for data exploration
  • ETL, CDC, and data warehousing tooling
  • designing and delivering data-driven solutions
  • extracting actionable insights from large datasets
  • presenting findings through clear visualisations

Nice-to-have

  • fraud prevention, detection or investigation
  • collaboration across fraud, data technology
  • apply knowledge of Spark, Databricks
  • working across time zones
  • Barclays Values and Mindset

Key Requirements

  • Experience with SAS and SQL
  • Experience with data management techniques
  • Experience capturing and translating business needs
  • Experience in fraud prevention, detection or investigation
  • Certifications in SAS, AWS, or Python
  • Knowledge of ETL and data warehousing
  • Data visualisation with Tableau or Power BI

Work Rights

Not specified

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