Data Scientist
Role Overview
The Data Scientist scopes, designs, and implements machine-learning models to support business use cases.
The role collaborates with product owners, business translators, data warehousing, and data engineering teams.
The role owns end-to-end model delivery, testing, and maintenance, and helps communicate model design and outputs.
The role includes mentoring junior team members.
Key Skills for This Role
Full Job Posting
Organization and analytics center
Emirates NBD established an Advanced Analytics Centre of Excellence to advance analytics across the bank.
The center works with business units to ideate, prioritize, pilot, and productionalize analytics projects through cross-functional squads.
The center aims to deliver business impact and build organization-wide advanced analytics capabilities.
Role purpose
The Data Scientist scopes, designs, and implements machine-learning models to support business use cases.
The role collaborates with product owners, business translators, data warehousing, and data engineering teams.
The role owns end-to-end model delivery, testing, and maintenance, and helps communicate model design and outputs.
The role includes mentoring junior team members.
Key responsibilities
- Deliver analytics projects with business units and build models that support business initiatives.
- Use structured and unstructured data, design data architecture, and experiment with machine-learning techniques.
- Document reusable code and maintain analytical models as business needs change.
- Share knowledge internally and externally, participate in meetups and conferences, and help plan team cultural initiatives.
- Guide junior colleagues in executing their duties and developing professionally.
Education and experience
- A university degree is required.
- An advanced degree in Computer Applications, Economics, Statistics, Mathematics, or a related technical discipline is desirable.
- Six to eight years of experience in a data science role is essential.
Knowledge and skills
- Experience defining analytics roadmaps and leading analytics engagements.
- Experience in machine learning, statistics, optimization, or related fields.
- Programming experience in R or Python is required.
- Experience with large datasets and simulation, optimization, or distributed computing tools such as MapReduce, Hadoop, Hive, or Spark is essential.
- Strong analytical and problem-solving skills, and experience working in agile environments with business stakeholders.
- Behavioral competencies include practical action, communication, stakeholder management, curiosity, teamwork, and quick learning.
Work flexibility
- The employer describes a flexible work policy that allows employees to work from home when it suits them.
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