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Data Scientist (Fraud/Anomaly Detection)
Job description
I am seeking a Data Scientist for the R&D team of a major financial company.
This is for a new team, operating as a cross-departmental, internal consultancy, working on research into company security/fraud/anti-financial crime and other related areas dependent on anomaly detection techniques in particular.
The role requires a strong understanding of large-scale finance/insurance organisations, along with a very advanced level of data analytics, particularly to include Machine Learning for Anomaly Detection and Big Data querying tools.
This role will give you the chance to work on a wide range of tools, across all aspects of a global business with significant, tangible outputs.
Requirements:
This is for a new team, operating as a cross-departmental, internal consultancy, working on research into company security/fraud/anti-financial crime and other related areas dependent on anomaly detection techniques in particular.
The role requires a strong understanding of large-scale finance/insurance organisations, along with a very advanced level of data analytics, particularly to include Machine Learning for Anomaly Detection and Big Data querying tools.
This role will give you the chance to work on a wide range of tools, across all aspects of a global business with significant, tangible outputs.
Requirements:
- A PhD in a relevant field and 1-2+ years commercial data science experience with a fraud/finance/insurance focus, or a Master's and 3+ years experience.
- Extensive experience with both Python and R, along with Big Data querying tools such as Hive/Impala
- Experience working in an Agile environment, particularly Scrum