Job Description

Our client who is a leading government entity in Abu Dhabi is looking to hire a Data Scientist who will be responsible to mine, clean, model, and interpret data to deliver that business insight to business users through relevant dashboards and reports

Responsibilities:

- Collaborate with product design and engineering to develop an understand business users' needs
- Research and devise innovative statistical models for data analysis using advance Machine Learning, NLP and AI technologies
- Design, develop and implement end-to-end machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building and performance evaluation)
- Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through business capabilities and work closely with the engineering team to strategize and execute the development of data products
- Identify relevant data sources and sets to mine for business needs, and collect large structured and unstructured datasets and variables
- Analyse data for trends, patterns and interpret data and develop advanced and accurate prediction algorithms with a clear business objective
- Plan, supervise and coordinate all activities in the assigned area to meet functional objectives
- Design and implement new tools and techniques to improve the quality and efficiency of operational processes

Requirements:

- Bachelor's degree in statistics, applied mathematics, or related discipline
- Master's degree in stats, applied math, or related discipline
- 7+ years of experience in data science
- Proficiency with data mining, mathematics, and advanced statistical analysis
- Advanced pattern recognition and predictive modelling experience
- Experience with Machine Learning in Python for forecasting and optimization
- Extensive experience with SQL, Phyton and other programming languages
- Familiar with Spark, Pandas, TensorFlow, Analysis Services, GitLab
- Ideally a UAE national with family book is preferred for the role