Data Scientist ML, 3886

Mindtel; Dubai; On-site; AED 250,000 - 350,000; Full time

Job summary

Mindtel in Dubai seeks a Senior Data Scientist Machine Learning to design, develop and productionize AI/ML models that impact business metrics. You will manage the full lifecycle from framing problems to deployment, using MLOps best practices and monitoring for performance.

Expertise in deep learning, statistical methods and Responsible AI principles is required, especially for regulated industries such as aviation or transportation. Proficiency with Python, R, SQL and ML frameworks is expected.

Qualifications

• Experience designing and deploying AI/ML models with measurable business impact.
• Experience managing the full AI/ML lifecycle from problem framing to deployment.
• Familiarity with MLOps best practices and monitoring models post-launch.

Responsibilities

• Design, develop and productionize AI/ML models that drive measurable business impact.
• Manage the full AI/ML lifecycle: framing business problems, preparing datasets, model training and deployment using MLOps.
• Monitor model performance post-launch to ensure accuracy and alignment with business objectives.
• Translate complex business requirements into actionable AI solutions.

Skills

AI/ML lifecycle

Problem framing

Model monitoring

Tools

Python

R

SQL

TensorFlow

PyTorch

Keras

scikit-learn

Hugging Face

Docker

Kubernetes

Git

CI/CD

Streamlit

Job description

Job Summary (Senior Data Scientist Machine Learning):

• - Design develop and productionize AI/ML models that drive measurable business impact.
• - Manage the full AI/ML lifecycle: framing business problems shaping and preparing datasets model training and deployment using MLOps best practices.
• - Monitor model performance post-launch to ensure accuracy reliability and alignment with business objectives.
• - Translate complex business requirements into actionable AI solutions.
• - Promote transparency across key AI/ML processes and performance indicators.
• - Apply expertise in deep learning statistical methods and Responsible AI principles especially in regulated industries such as aviation or transportation.
• - Use tools such as Python R SQL TensorFlow PyTorch Keras scikit-learn Hugging Face Docker Kubernetes Git CI/CD and Streamlit for end-to-end ML development and deployment.