Roles and Responsibilities:

1. Experience in performing analytics for a range of forensic investigations to identify red flags and evidences of fraud through data analytics.
2. Strong expertise in database management software (e.g. SQL Server, Oracle etc.), statistics and machine learning software (e.g. Python, R etc.) and link analysis/data visualization software, big data platforms (e.g. Hadoop, Hana);
3. Knowledge in data collection and load, data QA, data cleansing and enhancing, data transformation, relationship profiling, sampling and extrapolation, segmentation, modelling, segmentation, structured data mining and text mining. Exposure to ETL tools such as Informatica, SSIS, or scripting languages would be beneficial;
4. Experience in building dashboards with Tableau, QlikView, Power BI, Spotfire etc.
5. Strong knowledge of SQL and relational databases, as well as knowledge of predictive modelling technologies and machine learning such as SAS Enterprise Miner and other Open Source solutions etc.
6. Exposure to data from accounting systems application such as SAP, Oracle / PeopleSoft, JD Edwards etc.
7. Exposure to developing on-prem or cloud solutions for fraud detection and prevention across sectors.

Additional skills and attributes to success:

• Managing the key components of a portfolio of Forensic Technology projects, including strategy, planning and execution;
• Developing long-term relationships across a network of existing and potential clients, understanding their businesses to provide tailored insights;
• Constantly developing your understanding of our clients’ industries, identifying trends, risks and opportunities for improvement;
• Developing your team through constant coaching and feedback, providing challenging goals and guaranteeing your people have the skills, knowledge and opportunities to grow.

QUALIFICATION

• Technical Graduate and Post- Graduate from an accredited college/university.
• 0 to 2 Years of relevant experience.