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Our friends at Fortis will soon publish an interesting vacancy for a datascientist.
Recruiting a data science specialist
We currently have a job opportunity available for a data science specialist within the Analytical & Predictive Marketing team, which is part of the marketing department. As a Data Scientist you will be responsible for analytical projects which share the common goal of supporting and improving the bank’s marketing strategy, based on objective data analyses.
The Analytical & Predictive Marketing team plays an important role within the marketing department of BNP Paribas Fortis (Retail & Private Banking).
The main missions of the team are:
• Transformation, combination and exploitation of our raw customers data based on data mining techniques, in order to extract information allowing to guide and support the marketing strategy.
• Together with the Customer Intelligence teams (Market Research, Data Analysis, Customer Strategy and Pricing) increasing the customer knowledge by delivering clear customer information, based on indicators, recommendations, customer segmentation and customer profiling.
• Automating and integrating predictive models and other project’s output within the bank’s processes.
• Finding and proposing innovative analytical solutions, based on internal and external data, in order to increase customer satisfaction and optimize the marketing strategy
Projects and analysis are conducted in close relation with the other Marketing departments, such as Value Proposition, Campaign Management, Digital Channels, etc. These ensure that our pricing, product propositions and commercial actions are optimized, allowing us to increase customer satisfaction and loyalty.
Your future job
You will lead or be involved into projects related to:
• Improving and optimizing commercial actions through the creation of predictive models (e.g. appetite models), the objective evaluation of campaigns and the formulation of recommendations that are based on internal data analysis and your own experience.
• Creating customer indicators, based on models and different data sources, that allow both the branches and marketing to proactively and reactively respond to customer behavior correctly
• Provide analytical solutions to support important marketing decisions such as customer segmentation, price optimization, etc.
• Promote and improve the analytical approach in the long-term strategy of the bank as well as demonstrating its added value in terms of competitiveness
You are responsible for scheduling and implementing your project, and communicating its results. During the project, you will work closely with our internal customers (the other marketing departments) and communicate regularly on the progress and results of the project. A part of your time will be spent on R&D projects chosen by the team
• You have a university degree within one or more of these orientations: data science/data mining, analytical marketing, statistics, engineering or computer science.
• You have at least 3 years of experience in a similar function
• You are passionate by retrieving pertinent information from large data bases and to convey these insights in a comprehensible manner to answer our internal customer’s questions.
• You are proactively interested in the challenges of the company and are willing to provide analytical solutions
• You are creative and results driven
• You are a team player and you are able to work autonomously as well
• You are mastering several data science/data mining techniques: supervised and non-supervised learning, statistical analyses, Big Data architecture and concepts
• You are able to manipulate large data warehouses by programming (SAS, SQL, R, Python,…) and you have experience with data visualization tools (SpotFire,…)
• You are able to communicate in a clear and simple way. You are able to convey complicated analyses on a didactic and clear way to our internal customers.
• A good knowledge of the two national languages and of English is desirable.
How to apply?
Apply Now – or send your cv to Philippe (email@example.com) in case it is not published yet
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