Your role & work environment
You will be working for the Data Science chapter: a young and dynamic team of T-shaped professionals, who take care of the further development of data-driven innovation. The team uses a comprehensive data and application infrastructure, up to date with the latest developments in the open-source domain. The ultimate success of the team is determined mainly by the way its insights, algorithms & applications are used within ING.
To expand our chapter, we are looking for a junior / medior / senior data scientist to fulfill an end-to-end role. First, together with your colleague data scientists, you will be working actively within the business units of the bank, supporting their targets with data-driven solutions. Second, you will be working actively together with the machine learning engineers. In this part of your role, you will be able to focus on technical excellence of your work and you will be enabled to develop tools which expand our data-science capabilities.
Your key responsibilities
Analyzing a variety of internal and external data sources
- Determine the scope of different initiatives in collaboration with the relevant stakeholder in the segment, service or support tribes.
- Treat and analyze data using statistics / machine-learning techniques through specialized data-science tooling on a Hadoop cluster (Python, Spark, Hive, Jupyter, etc.) or GCP environment (BigQuery, Dataproc, etc).
- Search for new (open) data sources to enrich the analysis.
Advising: from data to insights to actions
- Translate the presented business problem to an analytical approach. Think of business problems such as identifying specific client behavior or needs, further personalizing our commercial approach, improving our internal process efficiency through automation / digitalization, etc.
- Transform these analyses into comprehensible information, define actions, formulate advice and present this to the relevant stakeholders (including senior management).
- Bring your analytical solution to production.
Shaping the data-science profession and landscape
- Expand the data-science toolkit (e.g. concerning data-quality checks, model building / validation / monitoring, etc.)
- Introduce the latest community developments into your day-to-day work
We look for
Are you someone who …
- is extremely curious, and has a constant urge to learn
- is able to handle setbacks, a real sticker
- analyzes sharply, concise and to the point, and who knows how to convince others
- maintains the overview in complex, unclear situations
- is good at communicating, presenting and selling his/her ideas
- is enthusiastic, and a real team player
- quickly adopts new techniques and software
And you have as well …
- an academic master’s degree with a focus on math/statistics/ econometrics/computer science (preferably with specific attention for machine learning and/or artificial intelligence)
- at least 1 year of relevant experience in corporate analytics.
- strong project-management skills allowing you to work independently and end-to-end
- experience with agile / scrum is considered a plus.
- knowledge of and experience with data-science technology. Experience with Python is crucial. Knowledge of and experience with Spark is considered a plus.
- demonstrable knowledge of and experience with statistics and/or machine learning.
- a grounded knowledge of English; Dutch and/or French is a plus.
… then you are our new Data Scientist.
What we offer
- the opportunity to have an impact on one of the key players in the Belgian financial industry, as well as collaborate on an international level with our data-science colleagues from other ING entities.
- challenging and diverse job content, both in terms of business domains to work for (Marketing, Credit Risk, Investments, Channels, KYC, etc.) as well as techniques to apply (supervised learning, unsupervised learning, time series, deep learning, NLP, etc.)
- an environment where 20% of your time can be dedicated to your own personal development and to self-chosen initiatives contributing to ING’s success.
- flexible working hours and the opportunity to work from home
- a young team of colleague data scientists with different backgrounds, whom combine ambition and drive with a dose of fun and humor
- an interesting salary package, including a diversity of financial and non-financial benefits