Job Description

Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United A"rab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group's entrepreneurship and relentless customer focus enables the organisation to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.
By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day.
Overview of the role
The purpose of the role is to lead the development and deployment of cross-functional data science use cases at Al Futtaim Group (AFG). Reporting to the Head of Data Science, the Senior Data Scientist will leverage AI and cloud technologies for ROI maximization through executing forecasting, predictive and optimization analytics models. The role holder will support in coaching/training junior data scientists and developing a set of standards/protocols to ensure that the data science practice is scalable and future-proof.
What you will do

• Work closely with the head of data science, head of analytics strategy and, potentially vendors, to identify analytics opportunities based on a deep understanding of AFG businesses and their information assets.
• Lead the delivery of use cases by proposing and delivering advanced analytic models, utilizing a blend of contemporary and traditional data mining techniques, applied to both structured and unstructured data sets.
• This includes, conducting data quality assessments, sharing relevant insights with business stakeholders, creating model monitoring solutions and conducting QA on other data science models (built internally or through 3rd party vendors).
• Implement models by transforming/optimizing for performance code and deploying them into production.
• Provide guidance, training and coaching to junior data scientists and the analytics community on data science frameworks, best practices, and technologies.
• Support in the development of analytics standards and protocols to ensure scalability and support self-service advanced analytics.
• Research and stay up to date on latest data science and analytics approaches and practices in the market ensuring that, when relevant, these are appropriately leveraged within Data and Analytics function.