Job Overview
As a Data Modeler in the Lending Tribe, you will find your home base in the Data Modeler 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 Modelers 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 database
Reporting and Automation
- Produce data models using SQL, and other tool
- 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 database
Industry Interaction
- Collaborate with data analysts, data scientists, and industry expert
- 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 case
Additional activities (Senior Candidates)
- Identify new opportunities to improve the domain critical key performance indicator
- Act as a data subject matter expert for designated product space/are
- 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 Mode
- Ability to work collaboratively with data engineers and scientists
- Ability to work effectively in a team environment
This is a plus
- Proficiency in Loan IQ
- Experience in the banking domain
- Skills to communicate complex ideas effectively
- Attitude to thrive in the ING “way of working” (e.g., Agile, small iteration)
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 experience
Skills
- Proficiency in SQL and relational database
- Advanced knowledge of data analysis, statistical techniques, and data mining
- Proficiency in PowerBI or Cognos is a plus
Job Overview
As a Data Modeler in the Lending Tribe, you will find your home base in the Data Modeler 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 Modelers 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 database
Reporting and Automation
- Produce data models using SQL, and other tool
- 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 database
Industry Interaction
- Collaborate with data analysts, data scientists, and industry expert
- 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 case
Additional activities (Senior Candidates)
- Identify new opportunities to improve the domain critical key performance indicator
- Act as a data subject matter expert for designated product space/are
- 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 Mode
- Ability to work collaboratively with data engineers and scientists
- Ability to work effectively in a team environment
This is a plus
- Proficiency in Loan IQ
- Experience in the banking domain
- Skills to communicate complex ideas effectively
- Attitude to thrive in the ING “way of working” (e.g., Agile, small iteration)
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 experience
Skills
- Proficiency in SQL and relational database
- Advanced knowledge of data analysis, statistical techniques, and data mining
- Proficiency in PowerBI or Cognos is a plus