Data Modeler

Bank of Singapore opens doors to new opportunities.

At Bank of Singapore, we are constantly on the lookout for exceptional individuals to join our team. We promote a culture of openness, teamwork and fairness. Most importantly, we invest in our people through our programmes that develop them on both professional and personal levels. Besides attractive remuneration packages, we offer non-financial benefits and opportunities to develop your potential within OCBC Group's global network of subsidiaries and offices. If you have passion, drive and the will to succeed, rise to the challenge today

This is an essential role that supports Bank of Singapore's ambition to be a data-driven company, leveraging high quality and timely client data and analytics to further advance our competitive advantage.

If you have a strong interest and the knowledge in using analytical tools to drive quality assurance, are passionate about driving data quality and process improvements, and have a knack for problem-solving, this is the opportunity for you. As data is deemed as a strategic asset for Bank of Singapore, this candidate should be a thought leader who will understand and solve identified business problems from curated datasets.

You will work with data and design architects to design and implement our data infrastructure for our new and existing platforms. You will be responsible for creating and maintaining data models for our databases, developing scripts for data cleansing, and developing tools to automate data entry.

Main Duties

•  Part of a new central team within the bank, the candidate will support the Head of Client Data in the data governance and formulation of information strategy.  Expected outcomes are data-driven business innovation and transformation.

• Work with the business intelligence team to gather requirements for database design and model

• Collaborate with the development team to design and build the database model

• Engage the development team to implement the database

• Determine the business needs for data reporting requirements

• Understand the Bank's data migration needs

• Work with the development team to implement the migration

• Work with data scientists to determine metadata querying requirements

• With technology changing at a rapid pace, the candidate is also expected to keep up with the latest innovation in data architecture and tools and lead the analysis and governance of the bank's data assets.

Other duties include:

• Support the Client Data team on data related requests, interpret data and turn it into information which can offer ways to help solve business problems or formulate data-driven decisions/strategies.

• Conduct data model reviews and provide feedback for improvement.

• Document and communicate data models and their specifications.

• Use data modeling tools and software for model creation (eg: ERDs) and management.

• Stay current with industry trends and emerging technologies to keep data models updated.

Work Experience Requirements

• Minimum 5 years of working experience with AI, ML, Data Science or a related field.

• Experience in applying machine learning techniques and designing algorithms that are scalable and production-grade.

• Experience with data modeling tools such as ER/Studio, ERwin, or PowerDesigner.

• Strong knowledge of SQL and database management systems like Oracle, SQL Server, or MySQL.

• Understanding of data warehousing concepts.

• Experience with big data technologies like Hadoop or Spark is a plus.

• Working experience with analytical tools and languages such as Python scikit-learn, R, SAS ML or equivalents.

• Knowledge of ETL processes and data integration

• Fine eye for detail with the ability to work with structured and unstructured data, including internal and external data.

• Experience with operating in a corporate environment and stakeholder management.

• Prior exposure to wealth management, asset management or portfolio management is a plus.

• Strong results driven personality with an innovative spirit.

Education Requirements

• Graduate or Postgraduate degree in Engineering, Statistics, Mathematics, Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS) or a related field.

Graduate or Postgraduate degree in Engineering, Statistics, Mathematics, Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS) or a related field.