Financial Crime / Fraud Analytics Director - London

B C T Resourcing
London (Greater)
13 Feb 2018
15 Mar 2018
Contract Type
Full Time
Director - Financial Crime / Fraud Analytics
120,000-160,000 + Package

An excellent opportunity has arisen for a Director to work for a global organisation operating in numerous industries, primarily banking. Our client is seeking tenacious, enthusiastic and driven individuals looking to progress and develop their career with an entrepreneurial attitude.

As a global organisation, they are looking to hire an experienced professional to lead a team at the pinnacle of advanced analytics within the Financial Crime , Fraud and Anti-money Laundering space. Candidates will have experience applying modern/ predictive learning/ machine learning, data science / AI techniques in this area and come from a strong quantitative academic background such as Mathematics, Economics, Statistics, Physics, Computer Science etc from a reputable university.

Key Responsibilities

You will be pivotal in supporting the business and leading a team of a group of exceptional talent within the advanced analytics umbrella, applying cutting edge , predictive learning / machine learning techniques in the Financial Crime Analytics space.

Key Requirements

* Extensive experience in a Financial Crime Analytics role within a financial market - Investment Banking, Banking, Asset Management , Fund Management - Looking at Fraud / Anti money laundering solutions.
* Masters Degree or high level qualification in a Quantitative related field such as Mathematics, Economics, Statistics, Computer Science or a other advanced scientific degree.
* PhD Advantageous
* Strong experience applying cutting edge techniques within on of the following areas - Machine Learning, Predictive Learning, AI, Deep Learning / Data Science.
* Competent with advanced analytical software such as SAS/ R / Python
* Proven experience delivering machine learning algorithms in this space

Keywords: Machine Learning, Predictive Learning, AI, Deep Learning, Data Science, Financial Crime, Fraud, Anti money laundering, analytics, quantitative analytics
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