Forensic Data Analytics Associate — Investigations & Insights

EY; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

EY Forensic & Integrity Services seeks a data analytics professional to collect and analyze large data sets across ERP and accounting systems. You will work with clients, investigators and regulators to identify fraud, anomalies and regulatory risks, while applying a range of visualization and analytical techniques.

You will build end-to-end data analysis pipelines, deliver actionable insights, and contribute to documentation and knowledge sharing within a multidisciplinary team.

Qualifications

• Degree in Computer Science, IT or related field.
• Solid knowledge of SQL and a broad awareness of programming languages such as Python, R as well as Visualization techniques
• Strong verbal and written communication skills
• Ability to travel

Responsibilities

• Collect and analyse large volume of structured and unstructured data from ERP and accounting systems.
• Collaborate with clients, investigators, auditors, lawyers and regulators to identify evidence of fraud and wastage.
• Analyse and mine data to identify known and unknown patterns of fraud.
• Execute end-to-end data analysis using ETL, visualization and deployment tools.
• Prepare working papers, schedules and reports to communicate findings clearly.

Skills

SQL

Python

R

Visualization techniques

Education

Bachelor's degree in Computer Science, IT or related field

Tools

SQL Server

PostgreSQL

Oracle

MySQL

Spotfire

Tableau

Power BI

Azure

AWS

Spark

Elasticsearch

Hadoop

Job description

EY Forensic & Integrity Services seeks a data analytics professional to collect and analyze large data sets across ERP and accounting systems. You will work with clients, investigators and regulators to identify fraud, anomalies and regulatory risks, while applying a range of visualization and analytical techniques.

You will build end-to-end data analysis pipelines, deliver actionable insights, and contribute to documentation and knowledge sharing within a multidisciplinary team.