Data Modeler

1 week ago

Makati City, National Capital Region, Philippines ING Hubs Philippines Full time

As a Data Modeller in the Lending Tribe, you will find your home base in the Data Modeller Center of Expertise. From there, you will serve a squad in one of the dedicated product areas or expertise centers, addressing their data modeling needs.

Data Modellers are responsible for designing, developing, and maintaining data models in relational databases and unstructured forms to enable innovative problem-solving, insights, behavior models, and communicating how those findings support improvements in decision-making, reliability, customer experience, profitability, etc.

Key Responsibilities

  • Data Modeling and Collaboration:
    • Act as a bridge between analytics and IT teams, bringing a data-driven perspective to the business.
    • Leverage data modeling skills to create data models that would serve the Data Engineers to build new databases.
  • Reporting and Automation:
    • Produce data models using SQL, and other tools.
    • Develop and automate tables serving as a base for regular updates (weekly, monthly, quarterly, and annually).
  • Data Structure and Applications:
    • Design and enhance data structures to ensure accuracy and integrity.
    • Modify applications to extract relevant information from company databases.
  • Industry Interaction:
    • Collaborate with data analysts, data scientists, and industry experts.
    • Understand how data should be transformed, loaded, and presented.
  • Mentoring and Innovation (Senior Candidates):
    • Mentor junior colleagues.
    • Collaborate with different teams to define new data modeling use cases.
  • Additional activities (Senior Candidates):
    • Identify new opportunities to improve the domain critical key performance indicators.
    • Act as a data subject matter expert for designated product space/area.
    • Engage with business users and product owners, understand problem statement, and then develop a customer-driven solution.
    • Research and analyze best-in-class industry solutions to design data-driven digital strategies for the bank.

Key Capabilities/Experience

  • Experience in analytical work with large datasets and relational databases (SQL).
  • Experience with data preparation (e.g., mapping) and data modeling/analysis (e.g., Entity-Relationship Model).
  • Ability to work collaboratively with data engineers and scientists.
  • Ability to work effectively in a team environment.
  • This is a plus:
    • Proficiency in LoanIQ
    • Experience in the banking domain.
    • Skills to communicate complex ideas effectively.
    • Attitude to thrive in the ING "way of working" (e.g., Agile, small iterations).

Minimum Qualifications

  • Education/Work Experience:
    • Bachelor's degree in a quantitative field such as Statistics, Computer Science, Engineering, Mathematics, or a related field. An advanced degree (e.g., Master, PhD) or a strong academic record with advanced coursework in Math, Statistics, or data management is a strong plus.
    • 2+ years of work experience in a data-related position.
    • For a Senior role: 5+ years of work experience in a data-related position within a banking team, working with business and technical experts.
  • Skills:
    • Proficiency in SQL and relational databases.
    • Advanced knowledge of data analysis, statistical techniques, and data mining.
    • Proficiency in PowerBI or Cognos is a plus.

We hire people like you for your potential. Our biggest expectation is that you'll stay curious. Keep learning. Take on more responsibility. In return, we'll back you to develop into an even more awesome version of yourself. With around 57,000 employees in over 40 countries, there is no shortage of opportunities. Show us initiative and we'll let you make a difference. ING is a great place to join. We work in a highly dynamic environment where people are trusted to make decisions and every voice gets heard. If you have an idea how to make things better, you'll be encouraged to make it happen – regardless of your position.
We'd love to meet you.

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