Description
Data Scientist/Engineer, Data Analytics, R, Spark, Hadoop, Bank, Brussels
Background:
You will join the Data Analytics team which is responsible for all Big Data and Analytics related matters throughout the bank and is in charge of collecting, analysing and reporting data in the context of Advanced Analytics.
Tasks:
As a member of the Data Analytics team, you will be curious, collaborative and innovative which is the mindset of the team. The role of the data scientist is pivotal in transforming a business question or gap into deliverables such as analytical tools, predictive models, etc that will generate actionable insight for business users.
Methods used are, amongst others, machine learning, natural language processing, fuzzy matching, etc
You must be flexible and manage multi-dimensional data sources and formats as well as a large panel of Analytics techniques commonly applied in Operational, Risk and client Analytics. As a Data Scientist at the bank, you work in close collaboration with internal business users to provide them with extended business insight serving their purposes. Your core objectives are to create value out of data and to experiment new technologies in order to develop capabilities within the company.
Manipulate internal and external data sources and conduct Data Analysis in order to produce quality and actionable outputs in a timely manner (around 8 weeks per case);
Build models to process varied and massive data sets using Big Data technologies;
Build tools for enhanced data visualization and trend reporting;
Deliver Analytics results and tools as intelligence that is actionable by business end-users;
Actively participate in the assessment of the evolution of the bank's Analytics platform in terms of software.
Contribute to new ideas (products) development and piloting.
Essential Skills:
Degree or equivalent experience in statistics, applied mathematics, or a related quantitative field;
2 years of experience in data analysis;
2 years of experience with open source statistical programming languages (eg. R);
Experience in data transformation;
Familiarity with data mining techniques;
Work experience using applied machine learning or statistical modelling; knowledge of algorithms spanning clustering, regression, classification, mixture models, graphical models, Bayesian statistics, and probabilistic modelling;
Experience with command line tools, relational databases (SQL), data visualization, and version control (eg. git).
Knowledge of and experience with classic and new/emerging Business Intelligence methodologies.
Language: English;
You must be an EU national to apply for this role.