Data Scientist
Role Overview
The Data Scientist scopes, designs, and implements machine-learning models to support business use cases and organizational objectives.
The role works with product owners, business translators, data warehousing, and data engineering teams to create big data applications.
The role includes end-to-end model delivery and communicating model design, functioning, and output to business translators.
Key Skills for This Role
Full Job Posting
Organization and analytics center
The posting describes Emirates NBD as a large Middle East bank with global operations.
Its Advanced Analytics Centre of Excellence is tasked with advancing analytics across the organization and building data-driven capabilities.
The center works with business units to ideate, prioritize, pilot, and productionalize advanced analytics use cases through cross-functional squads.
The center's objectives include delivering business impact through analytics projects and building organization-wide advanced analytics capability.
The analytics agenda is described as a high-priority initiative governed at executive committee level, with impact tracking, a ring-fenced budget, and performance management.
Role purpose
The Data Scientist scopes, designs, and implements machine-learning models to support business use cases and organizational objectives.
The role works with product owners, business translators, data warehousing, and data engineering teams to create big data applications.
The role includes end-to-end model delivery and communicating model design, functioning, and output to business translators.
Core responsibilities
- Design and implement machine-learning models for business initiatives and contribute to the advanced analytics project roadmap with business units.
- Use structured and unstructured data, contribute to data architecture, and experiment with machine-learning techniques.
- Test and maintain analytical models regularly to improve efficiency and respond to changing business needs.
- Document reusable code and help stakeholders understand developed analytical models and solutions.
- Mentor junior colleagues and support their professional growth.
- Conduct knowledge-sharing sessions within the center and externally at meetups and conferences.
- Pursue personal technical development and learning goals and help plan center cultural initiatives.
Requirements
- Ability to scope, design, and implement machine-learning models for business use cases.
- Ability to deliver machine-learning models end to end, including regular testing and maintenance.
- Ability to work collaboratively with product owners, business translators, data warehousing teams, and data engineering teams.
- Ability to work with structured and unstructured data and contribute to data architecture for big data applications.
- Ability to document reusable code and communicate analytical model design, function, and output to stakeholders.
- Willingness to contribute to team learning, knowledge sharing, and mentoring junior colleagues.
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