Senior Data Scientist Jobs in Dubai | Majid Al Futtaim
Job Responsibilities:
Lead a team of 4+ data scientists & external vendor consultants while delivering effective analytical solutions to complex business problems for the Retail/ Properties/ Leisure, Entertainment & Lifestyle sectors
Provide oversight/ carry out hands-on development of Predictive Models, Segmentation, Optimization algorithms, etc. using Machine Learning techniques on large volumes of structured and unstructured data.
Manage the delivery lifecycle while proactively identifying problems that may arise in the project, outlining options, recommending solutions, and escalating as needed
Champion the needs of business teams and stakeholders throughout the development process, ensuring deliverables are aligned with the original goals and objectives
Challenge current best thinking, test theories, evaluate data science and machine learning concepts and iterate rapidly while owning the deliverables and managing team’s priorities/timelines
Develop best practice analytic frameworks, tools and other assets by working with vendors, scale to other opcos
Draft policies & procedures / establish process adherence to Data Science workflows, model lifecycle management, technical documentation and knowledge repository management
Define the inventory of tools that data scientists use to deliver a use case with clear standards to handle an increasing heterogeneity of data science toolkits
Support advocacy of a data driven culture – Organize/participate in internal events, tech talks to increase the adoption of DS across MAF
Share and communicate – Create a medium where data achievements can be shared and celebrated with the community of Data Science practitioners
Provide technical expertise to federated analytics teams within MAF Opcos, fostering an environment of collaboration
Contribute towards building a culture that promotes continuous learning, development and retention of data science talent
Work closely with Data Engineering team to guide them on structuring relevant data to facilitate data exploration and fast prototyping, report data quality issues.
Collaborate with Product, DevOps and other teams to test, deploy, scale and monitor ML models as components to Data based products/ Use Cases
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