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Structuring our data team for success

Structuring our data team for success

  • 2 June 2022
  • By OCBC Careers
  • 10 mins read

To centralise or not to centralise is the key question that arises when it comes to structuring data teams.

The OCBC Data Office team structure has evolved over 20 years. We believe that centralising teams with specialised skills, like data science, is better for scalability as team members can collaborate and learn from one another. A large central team also allows analysts to continuously pick up new skills as they support different use cases across the Bank.

Our model enables Group Data Office to execute many use cases for all parts of the OCBC Group. We use shared platforms and a common analyst pool to create synergies to reuse data pipelines and models. This accelerates project delivery and gets us to market much faster.

- Donald MacDonald, Head, Group Data Office

Even with a centralised team, we maintain links with our key business units through strong relationships managed by Analytics Translators and by embedding data resources into ongoing Agile squad projects.

Group Data Office team structure

Key roles within the team

Analytics Translators:
Analytics Translators focus on partnering with business units to understand their business objectives and pain points. They are responsible for identifying and prioritising key problem statements for data to solve. Analytics Translators are expert data storytellers who help the business units understand the output from analytics and learn how to put it into action.

Data Analysts:
Data analysts are deeply integrated with the business units and ensure rapid turnaround of insights to enable better decision-making and more relevant customer communications. They are responsible for the development of analytical deep dives and profiling, segmentation, marketing campaigns, dashboards and digital insights.

Data Scientists:
Data Scientists (also known as The AI Lab) are responsible for more complex Data Science and AI projects – often involving unstructured information. They focus on key domain areas with dedicated teams covering subjects such as Personalisation, Monetisation, Conversational AI, Risk, Financial Crime and Smart Application (full stack) development. As production deployments are on a large scale, Data Scientists must possess both computer science skills as well as a traditional mathematical background.

Data Engineers:
Data Engineers are the bridge between the Data Team and IT Data Engineers. They manage the centralised data platform stack and develop data strategies that prioritise data integration roadmaps. Data Engineers also develop data fabric and application specific pipelines to make access to data as self-service as possible for Data Analysts and Scientists.

As a group resource, we work with all OCBC divisions and business units across the region, helping them maximise the potential for staff to work on new use cases and learn different aspects of the business.

To ensure long-term success, we hire from diverse experiences and backgrounds. To date, our team has over 20 different nationalities and a 60:40 gender mix.

If you’d like to work on interesting use cases with a top team, do check out the roles mentioned above.