Data Scientist
Job Description
We are seeking an experienced Data Scientist to join our team on an initial 6-month freelance contract. This is a hybrid opportunity based in the UAE, requiring regular onsite collaboration while offering flexibility for remote work.
Required Skills & Experience
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 4+ years of experience in Data Science, Machine Learning, or Advanced Analytics roles.
• Strong proficiency in Python and relevant data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Experience with SQL and working with large-scale databases.
• Strong understanding of machine learning algorithms, statistical analysis, and predictive modeling.
• Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud is an advantage.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently in a freelance consulting environment.
Preferred Qualifications
• Experience working in enterprise-scale environments.
• Familiarity with MLOps practices and model deployment processes.
• Experience with Big Data technologies such as Spark or Databricks.
• Previous experience delivering projects within the UAE or GCC region.
Responsibilities Duties:
The successful candidate will be responsible for developing advanced analytical models, generating actionable business insights, and supporting data-driven decision-making across the organization.
Key Responsibilities
• Analyze large and complex datasets to identify trends, patterns, and business opportunities.
• Design, develop, and deploy machine learning and predictive analytics models.
• Collaborate with business stakeholders to understand requirements and translate them into data solutions.
• Build statistical models to solve business challenges and improve operational efficiency.
• Perform data cleansing, transformation, and validation to ensure data quality.
• Develop dashboards, reports, and visualizations to communicate findings effectively.
• Monitor and optimize model performance in production environments.
• Present insights and recommendations to technical and non-technical audiences.
• Support data strategy initiatives and contribute to best practices in data science and analytics.