Data Scientist, dnata Airport Operations

As Data Scientist, you will undertake Data Science (DS) projects through the application of mathematical modelling, machine learning, problem structuring, and big data analysis to solve complex business problems with a focus on timely delivery and ownership of results. This is a full-time role and is based in our Dubai office.

In this role, you will:

• Deliver analytics projects, applying appropriate statistical and machine learning techniques to produce key insights and actionable takeaways, and presenting findings and recommendations to the stakeholders.
• Develop dimensions of the DS project such as data analysis, visualization, and development of tools, models, and documentation. Analyse business metrics and KPIs to understand trends, identify issues, and opportunities for optimisation.
• Address day-to-day technical issues, ensuring high quality of deliveries are achieved.
• Derive business insight from large, structured, semi-structured, and unstructured data sets and work with business stakeholders to deploy insights derived from this analysis to extract commercial value.
• Work with cross-functional team members, combining computer science and mathematics, to identify and inject high-value actionable insights into business processes at their point of highest impact. Work in quick iterations, using the techniques and algorithms best suited for solving the challenging problems through active involvement in the development of our analytics tools for A/B testing, segmentation, funnel analysis, and other analytics needs.
• Support sprint/work design and planning projects to bridge the gap between research and analytics by providing data-driven solutions across the required areas.

To be considered for the role, you must meet the below requirements:

• Masters's degree in data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning, or economics.
• Minimum 2 to 4+ years of hands-on experience in the Analytics ecosystem.
• Hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (Tensorflow, Keras, etc.)
• Hands-on experience with SQL, R, Python, DevOps frameworks (Git, CI/CD, Docker).
• Proficient in building libraries and packages to be reused by others.
• Experience in building DS Solutions for production usage.
• Experience of delivering advanced analytical projects to large, complex organisations in a multifunctional environment.