全职 Data Analyst 工作, 薪水, HFG Insurance Recruitment Federal Territory 公司招聘中 - Ricebowl

Role: Data Analyst - Manager/Senior Manager

Role Overview

This role sits within the Risk Compliance Security Unit and reports directly to the Head of Group Risk Assurance & Data Analytics COE.

As a Data Analyst, you will be responsible for managing, analysing, and interpreting data to support informed decision-making. You will play a key role in transforming data into meaningful insights, producing regular reports, and contributing to strategic initiatives.

You will support Financial Crime Compliance (FCC) by designing and delivering analytics-driven solutions to enhance financial crime risk management, governance, monitoring, and reporting. This includes developing analytical models, strengthening monitoring capabilities, and supporting investigations through data-driven insights.

Key Responsibilities

• Gather and validate large datasets to ensure accuracy and consistency.
• Automate data preparation and cleansing processes to improve efficiency.
• Design, develop, and maintain AI-driven solutions such as agents and data feeds.
• Perform exploratory and in-depth data analysis to identify trends, risks, and anomalies in line with regulatory and risk frameworks.
• Analyse financial crime activities and provide actionable insights to stakeholders.
• Build and maintain data pipelines for financial crime detection and monitoring.
• Develop analytical tools and models to support monitoring and investigation processes.
• Work closely with Risk, Compliance, and IT teams to deliver data solutions.
• Create clear data visualisations and present insights effectively to senior stakeholders.
• Support audit and assurance activities by providing data-backed evidence.

Key Requirements

• Strong analytical and problem-solving capabilities, with a focus on product and solution development.
• Proficiency in statistical programming languages such as Python and SQL.
• Good understanding of machine learning techniques (e.g. clustering, decision trees, neural networks) and their practical applications.
• Solid knowledge of advanced statistical concepts (e.g. regression, statistical testing, distributions).
• Strong communication skills, both written and verbal.
• Experience working with distributed data environments.

Candidate Specification

• Bachelor’s, Master’s, or PhD in Statistics, Mathematics, Computer Science, or a related quantitative discipline.
• Minimum 5 years of experience handling large datasets and developing statistical models.
• Hands-on experience with programming languages such as Python, C, C++, Java, or JavaScript
• Familiarity with statistical and data mining techniques such as regression, random forest, boosting, decision trees, text mining, and network analysis.
• Experience applying advanced machine learning techniques including simulation, clustering, and neural networks.
• Exposure to big data tools such as Hadoop, Hive, or Spark.
• Proven ability to present and visualise data for business stakeholders.
• Professional certifications such as CAMS or ICA (Financial Crime) are advantageous
• Knowledge of financial crime domains including AML, CTF, sanctions, fraud, tax evasion, and anti-bribery and corruption.
• Understanding of non-financial risks, including operational and conduct risk.