Data Analyst/Scientist to Fraud Management, Stockholm or Helsink - Nordea Bank AB - Datajobb i Stockholm
Data Analyst/Scientist to Fraud Management, Stockholm or Helsink
Nordea Bank AB / Datajobb / Stockholm
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In Fraud Management, we are now looking for you who are passionate about extracting value from data, and turn it into actions and products in order to prevent financial fraud.

With your knowledge and engagement you will be a valuable contributor in working hands on with analytics problems within financial fraud, such as binary classification, business rules engines and time series forecasting.

The position we offer

In Fraud Management we are handling all customer related fraud prevention and monitoring, where we are preventing, detecting and resolving customer related fraud attempts and cases in all our customer channels.

As Data Analyst/Scientist, you will be part of implementing and working with fraud prevention solutions on a global level.

You will:

* Work hands on with various data sources and technologies, and create data-products, such as interactive reports and simulation tools.
* Evaluate and apply new technologies and solutions to existing problems.
* Make business and functional requirements towards our IT service provider
* Design algorithms and other business rules, and by that analyse and optimise existing rules in our detection systems.
* Give input to the strategic and daily work within Fraud Management, regarding development and operational work.
* Liaise with industry representatives, discussing new and innovative solutions in the prevention of fraud.
* Work close to and act as a subject matter expert towards projects and stakeholders, both internally and externally.

The position is located in Stockholm or Helsinki, and some travel might be required.

The qualifications you need

We are looking for you who are analytical skilled and motivated by finding patterns, links and trends, and extracting value from large scale data, as well as finding new and improved ways of doing so.

You are:

* Driven with a positive can-do attitude, and enjoy working both independently and in a team.
* Curious and a quick learner with the ambition to learn new tools and languages.
* Detail oriented, but can at the same time keep an overview of your work and manage changing priorities.
* Interested in working with big data and real-time or big data processing technology, for example, Spark, Hadoop.
* Interested in data mining, predictive modelling and other data science related areas.

You have:

* Mathematical and statistical knowledge and you can model real-world problems.
* Excellent skills in SQL and can translate business questions to database queries.
* Knowledge in RDMSes, data warehousing and Hadoop related technologies.
* A few years' experience of using R and/or Python.
* Good skills in Excel, mainly pivot tables, VBA and preferably in PowerPivot and DAX.

It will be considered a plus if you have any of the following:

* Experience of working with banking/financial institutions.
* Familiarity with Financial Anti-crime applications, and from financial real-time analytics and business intelligent platforms, together with statistical software packages.
* Ability to apply various data analytics concepts, from machine learning, pattern recognition, statistical analysis and hypothesis testing.
* Knowledge in functional programming concepts, such as Haskell, Scala, F#, Erlang.

Finally, you have a university degree in Computer Science, Mathematics, Physics or related fields. You have excellent English skills, both oral and written.

More information and send application

For more information about the position, please contact Rickard Edholm on

Please submit your application, including cover letter, CV and other relevant documents no later than 14 July, 2017, by using our online application form.

Varaktighet, arbetstid
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Så ansöker du
Sista dag att ansöka är 2017-07-14
Klicka på denna länk för att göra din ansökan

Rickard Edholm

Nordea Bank AB

Nordea Bank AB
Lindhagensgatan 112
10571 Stockholm

Lindhagensgatan 112


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