As a bank we collect vast amounts of data every day. Over the past years we’ve accelerated our efforts to become a truly data driven organization. One where each of us understands the value of data and how to apply it in their daily work. One that uses and stores data securely and responsibly. One that applies analytics to data to create actionable insights for our customers and improve our daily decision making. Using data insights to create a better customer experience is at the heart of ING’s strategy. A customer experience that is refreshingly smart, surprisingly personal and remarkably easy. It lets us do things like make customer interactions 100% personal and relevant. Verify client identities, predict credit risk… or make chatbots more responsive, human and helpful.
ING has set the ambition to become a data-driven organisation with analytics as a business model.
Data Fluency has been identified as one of the distinctive capabilities needed for ING to stand out in the market and are essential to create value for ING. It’s thus no surprise that all data / analytics teams put a strong focus on enriching the skillset and craftsmanship of their experts (analytical skills, machine learning skills, soft skills, bank knowledge, etc.).
In Belgium these roles are often linked to the Tribe Data management or the Tribe Digital Sales & Customer Interactions.
Tribe Data management
Within the data management tribe, our purpose is to bring data from producers of data to users of data, consistent with industry best practices, and in a compliant and ethical manner.
Within the different roles in the tribe (data quality officer, data governance,..) you will be involved in the whole lifecycle of a data set and will learn how data progresses and changes through the internal data streams of ING Belgium.
Additionally, with a well-developed Data Management programme, you will have the opportunity to positively effect change around the administration and use of data assets and to further develop your craftsmanship over time in the field of data and data science.
Tribe Digital Sales & Customer Interactions
In this tribe we let both our colleagues and customers benefit from insights from data to achieve their goals. The objective is to turn data into insights and actions.
We do this by using models, tools, machine learning, building dynamic dashboards and assigning specialists to complex issues.
As a data analyst, your mission is diverse. Even though you are centrally part of the tribe Digital Sales and CI, where you’ll be coached on craftmanship together with your analytics colleagues, you’ll be delivering impact across different business domains based on a flexible allocation process (Retail, Business Banking, Risk and COO).
This means that you could be working:
- With our business partners to increase services and sales through campaigns and lead management.
- On supporting our digital journey by working on customer experience, personalization and digital adoption.
- On risk mitigation by detecting money laundering practices, predicting credit risk or catching cybercriminals.
There are many options and flavours on how you can enable data driven decision making by senior stakeholders throughout the organization.
As a data scientist you are complementary to the missions of our data analysts. You’ll specifically support the data driven decision making throughout the organization by delivering data products based on complex data sources, machine learning and end-to-end pipelines. You’ll be in a key position to execute the change roadmap from an analytical perspective together with our senior stakeholders.
Organizationally, Digital Sales & CI is a tribe which is linked to ING Analytics, a global community across eight centres of expertise built around a common ambition:
- Scaling models across business lines and countries.
- Align modelling activities to the strategic goals of the business.
- Create a global community of expert data and analytics resources.
- Building a global integrated analytics capability, with a skill development and career framework.
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