Requirements
Requires 7-10 years of professional experience in data science or related roles, with a Bachelor’s degree in computer science, statistics, mathematics, or engineering. Must have advanced proficiency in Python (pandas, scikit-learn, TensorFlow/PyTorch), strong grasp of machine learning algorithms, statistical modeling, and data mining techniques, and hands-on experience with SQL and relational databases. Proven ability to work with large datasets, build end-to-end data pipelines, and communicate complex technical concepts clearly.
Description
Job description / Role
Job Type
Full Time
Job Location
Abu Dhabi, UAE
Nationality
Any Nationality
Salary
Not Specified
Gender
Not Specified
Arabic Fluency
Not Specified
Job Function
IT - Software & Web Development
Company Industry
Recruitment & HR
About the role:
We are seeking an experienced data scientist to join our Abu Dhabi team. In this role, you will leverage advanced data science and machine learning techniques to extract actionable insights, build predictive models, and drive strategic decision-making across the organization. You will collaborate with cross-functional teams, mentor junior analysts, and ensure the deployment of scalable solutions in a dynamic, fast-paced environment.
Responsibilities:
Design, develop, and deploy machine learning models and predictive analytics solutions
Analyze large and complex datasets to identify trends, patterns, and business opportunities
Collaborate with stakeholders to define data requirements and translate business problems into analytical solutions
Build and maintain data pipelines and ETL processes for model training and deployment
Validate model performance, conduct A/B testing, and monitor models in production
Communicate findings and recommendations through clear visualizations and presentations to both technical and non-technical audiences
Mentor junior data scientists and analysts, providing technical guidance and best practices
Required qualifications:
7–10 years of professional experience in data science or related roles
Bachelor’s degree in computer science, statistics, mathematics, engineering, or a related field
Advanced proficiency in Python and relevant libraries (pandas, scikit-learn, TensorFlow/PyTorch)
Strong grasp of machine learning algorithms, statistical modeling, and data mining techniques
Hands-on experience with SQL and working knowledge of relational databases
Proven ability to work with large datasets and build end-to-end data pipelines
Excellent problem-solving skills and the ability to communicate complex technical concepts clearly
Preferred qualifications:
Master’s or PhD in data science, machine learning, or a related discipline
Experience with cloud platforms such as AWS, Azure, or Google Cloud for data processing and model deployment
Familiarity with big data frameworks (Apache Spark, Hadoop)
Knowledge of MLOps practices, containerization (Docker, Kubernetes), and CI/CD pipelines
Experience in domain-specific applications (e.g., finance, energy, or oil & gas)
Proficiency with data visualization tools (Tableau, Power BI, D3.js)
Position details
Location: Abu Dhabi, United Arab Emirates
Industry: Information Technology (IT) / Software
Experience required: 7+ years
About the Company
AIQU connects future-ready technology specialists with forward-looking organisations. We help businesses deliver high-impact and high-quality technology projects by using our unrivalled global sourcing capabilities to attract diverse talent within the region.
Our bespoke staffing solution offers the most flexible option you can have while maintaining 100% legislative compliance. AIQU’s fast and highly responsive employee management processes are designed to provide your most valuable assets, your people, with a seamless experience!
From business analysts to change managers; from front-end developers to back-end engineers, full-stack developers, and database administrators; from process analysts to software architects; AIQU can provide and manage specialists for a technology transformation project or for a project in maintenance phase across six key verticals.
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