Data Scientist

Location: Client Premises, Dubai, UAE

Salary: AED 15,000 to 18,000 per month

Benefits: Work visa, air tickets, medical insurance, gratuity, paid time off

Experience Required: Minimum 5 years of relevant work experience

Reference: FZ-AE-130

You will design, build, and productionise machine-learning and generative-AI solutions that deliver high-value predictive insights. Working hands-on with Python, R, TensorFlow, PyTorch, AWS SageMaker, Bedrock, and modern GenAI frameworks, you will turn complex data into actionable intelligence for business and product stakeholders.

Key Responsibilities

• Design, train, and evaluate ML, deep-learning, and GenAI models for classification, regression, forecasting, and text/image generation.
• Rapidly iterate and benchmark performance using TensorFlow, PyTorch, Hugging Face, and LangChain.
• Build and maintain robust data pipelines with Python/R and SQL on AWS (Glue, Redshift, Athena) for both structured and unstructured data.
• Package and deploy models via SageMaker pipelines, Bedrock APIs, or custom Docker/Kubernetes workflows.
• Implement CI/CD, automated testing, monitoring, retraining triggers, and drift detection.
• Translate business objectives into analytic problems, define KPIs, and frame success metrics for predictive and generative use cases.
• Present insights through dashboards, notebooks, and concise executive briefings.
• Partner with product, engineering, and domain SMEs to embed intelligence in customer-facing products and internal tools.
• Evaluate emerging GenAI frameworks and lead proof-of-concepts to drive adoption of state-of-the-art techniques.
• Contribute to internal standards, reusable components, and knowledge-sharing sessions.

Required Skills & Qualifications

• Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, Engineering, or related field.
• Mathematics & Statistics: Strong foundation in probability, statistics, optimisation, and experiment design (A/B testing).
• Programming & Analytics: Expert proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and R; advanced SQL for complex data manipulation.
• Machine-Learning & Deep-Learning: 5+ years building, tuning, and deploying models with TensorFlow and/or PyTorch; solid grasp of feature engineering, hyper-parameter optimisation, and model evaluation.
• Cloud & MLOps: Production experience on AWS, especially SageMaker (training, tuning, pipelines, endpoints) and Bedrock; familiarity with Docker, ECR, CloudWatch, IAM, and CI/CD tools.
• GenAI & LLMs: Hands-on integration or fine-tuning of LLMs/diffusion models using Hugging Face Transformers, LangChain, or Bedrock-hosted models.
• Communication: Proven ability to distil complex analyses into clear, actionable insights for technical and non-technical audiences.