Senior Financial Crime Data Analytics & AI (Hybrid)

Bendigobank; Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work options

Health and wellbeing support

BEN U corporate university

Job summary

Bendigo Bank is seeking a Senior Analyst in Financial Crime Data Analytics & AI to safeguard customers by designing data, analytics and AI solutions for detecting financial crime. You will shape innovations and implement robust data-driven detection across our risk functions.

Role involves advanced analytics, machine learning model development and collaboration with Technology and Operations to embed compliant, proactive prevention strategies. Hybrid work with local attendance expectations.

Qualifications

• Strong data analytics, advanced analytics and detection scenario development.
• Excellent programming and database skills, with SQL proficiency.
• Ability to translate complex data and technical requirements to non-technical stakeholders.
• Degree in a STEM field or equivalent professional experience.

Responsibilities

• Analyse data to develop and improve detection solutions for financial crime threats.
• Utilise AI to enhance detection capabilities and identify trends.
• Collaborate with Risk, Technology and Operations to governance and implement analytics solutions.
• Lead discovery and estimation for analytics implementations related to new products and systems.

Skills

SQL

Python

Data analytics

Stakeholder comms

Problem solving

Education

STEM degree

Tools

Google Cloud Platform

R

SAS

Job description

Bendigo Bank is seeking a Senior Analyst in Financial Crime Data Analytics & AI to safeguard customers by designing data, analytics and AI solutions for detecting financial crime. You will shape innovations and implement robust data-driven detection across our risk functions.

Role involves advanced analytics, machine learning model development and collaboration with Technology and Operations to embed compliant, proactive prevention strategies. Hybrid work with local attendance expectations.