manager fraud investigation & dispute services in amsterdam

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vacature details

amsterdam, noord-holland
Financieel & Economisch
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The analytics team is a global group of technical specialists that practice the full life cycle of data management from the early stages of data scoping and capture, to its management, analysis and reporting. The nature of our work will typically require you to work with large datasets from varying data sources to support fraud investigations and disputes for our clients covering a range of industries. You will achieve this by combining deep forensic investigation knowledge with advanced data analytics techniques such as investigative data linking, social network analysis, statistics, artificial intelligence, machine learning and predictive modelling.

Forensic technology labs and datacentres provide leading forensic technology infrastructure and tools necessary to uncover the most complex cyber, compliance and fraud risks close to the occurrence.

Your key responsibilities
As a Manager Forensic Data Analytics, you’ll play a key role in the management and future growth of the department. Working with clients across all industries, you’ll develop innovative recommendations to some of the most challenging data issues around. Since we work with such a diverse portfolio of clients across industries, you can expect to take on a wide range of projects, making this a great place to enhance your personal experience, your technical skills and business knowledge.

It’s no exaggeration to say you’ll never be doing the same task for too long. You’re likely to balance your time between directly liaising with our clients to understand their needs and actively analyzing large structured and unstructured datasets. It’s all about using your technical skills to creatively assess and resolve our clients’ needs from the front lines. That means thinking differently about data-driven problem solving and speaking up with innovative ideas that challenge the status quo.
You will work and build strong relationships with the EY team including, lawyers, compliance specialists and fraud investigators together with clients, internal and external auditors, lawyers and regulatory authorities in sensitive and adversarial situations. 

Client offers a competitive remuneration package where you’ll be rewarded for your individual and team performance. The comprehensive Total Rewards package includes support for flexible working and career development. A career here is not like any other; with us, your competencies and your areas of interest will determine your future, plus we offer you:
  • A career within a global leading consulting and audit firm, working with prominent national and global institutions
  • A position with a high degree of autonomy and responsibility, and room for personal development


Skills and attributes for success
  • Managing the key components of a portfolio of Forensic Technology and Discovery Services 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.

To qualify for the role you must have
  • Strong academic record, including a degree in a relevant subject (e.g. Computer Science, Applied Mathematics, Artificial Intelligence, Statistics, Accounting and/or Finance);
  • Passionate about Data Analytics along with minimum of 5-7 years of experience in programming skills 5-7 year prior experience to any data analytics tools and techniques is also beneficial.

Ideally, you’ll also have
  • Exposure to database management software, stats and machine learning software and link analysis/data visualization software, big data platforms (e.g. Hadoop, Hana);
  • 5 year experience 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;
  • Strong knowledge of SQL and relational databases, as well as knowledge of predictive modelling technologies and machine learning such as SAS Enterprise Miner, SPSS, SQL Server, Open Source solutions etc.
  • Exposure to data from accounting systems application such as SAP, Oracle / PeopleSoft, JD Edwards etc.