Senior Machine Learning Scientist Senior Data Analytics Scientist Senior Applied Data Scientist

Q Mart | كيو; Dubai; Sur place; AED 480 000 - 840 000; Plein temps

Résumé du poste

Q Mart | كيو is seeking an experienced data scientist to develop and deploy advanced ML solutions that address complex business challenges in the Dubai area.

You will perform large-scale data analysis, build predictive models, and collaborate with engineering, product, and BI teams to translate business needs into scalable data-driven solutions. Strong communication and ethical AI practices are essential.

Qualifications

• Advanced degree in a data science related field.
• Strong statistical analysis and modeling skills.
• Experience with ML frameworks and Python/R.
• Ability to design and deploy ML solutions at scale.

Responsabilités

• Develop and implement data science and ML solutions to address business challenges.
• Conduct large-scale data analysis and predictive analytics for strategic decisions.
• Design, train, and optimize ML models to improve performance.
• Collaborate with engineering, product, BI and research teams.
• Lead experiments, evaluation, and governance for reproducibility.
• Maintain data pipelines and model deployment processes.
• Communicate findings and strategic recommendations to stakeholders.
• Explore new ML approaches and ensure ethical AI and data privacy compliance.

Connaissances

Python/R

Statistical analysis

ML algorithms

TensorFlow/PyTorch

SQL

MLOps

Data visualization

Communication

Formation

Master's or PhD in a relevant field (Data Science, CS, stats, AI)

Outils

TensorFlow

PyTorch

Scikit-learn

Description du poste

Role Description

• Develop and implement advanced data science and machine learning solutions to address complex business challenges and support strategic decision-making.
• Conduct large-scale data analysis, statistical modeling, and predictive analytics to identify patterns, trends, and actionable business insights.
• Design, develop, train, and optimize machine learning models and algorithms to improve business performance, operational efficiency, and product capabilities.
• Apply advanced analytical techniques, including supervised learning, unsupervised learning, deep learning, and natural language processing to solve real-world problems.
• Collaborate with engineering, product, business intelligence, and research teams to translate business requirements into scalable data-driven solutions.
• Lead analytical research initiatives, experiment design, hypothesis testing, and model evaluation to ensure accuracy, reliability, and practical applicability.
• Develop and maintain data pipelines, analytical frameworks, and model deployment processes to support efficient data science operations.
• Evaluate model performance, identify potential biases, and implement optimization strategies to improve prediction accuracy and model robustness.
• Utilize advanced statistical methods, feature engineering, and data visualization techniques to communicate findings and support business strategies.
• Explore emerging technologies, research methodologies, and innovative machine learning approaches to enhance analytical capabilities.
• Ensure data quality, model governance, reproducibility, and compliance with relevant data privacy and information security requirements.
• Work closely with technical stakeholders to integrate machine learning models into production systems and monitor their ongoing performance.
• Prepare technical reports, research findings, analytical presentations, and strategic recommendations for management and business stakeholders.
• Promote data-driven innovation and continuous improvement through advanced analytics, experimentation, and intelligent automation.

Qualifications

• Master's degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related discipline.
• Strong understanding of statistical analysis, probability theory, predictive modeling, and advanced data science methodologies.
• Proficiency in Python or R, with strong programming capabilities for data processing, statistical analysis, and machine learning development.
• Good knowledge of machine learning algorithms, deep learning architectures, neural networks, and model optimization techniques.
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, and related analytical libraries.
• Strong understanding of SQL, database management, data preprocessing, feature engineering, and data pipeline development.
• Knowledge of natural language processing, computer vision, recommendation systems, or other applied AI technologies is advantageous.
• Strong analytical thinking, research capabilities, and complex problem-solving skills.
• Familiarity with cloud computing platforms, MLOps, model deployment, and distributed data processing systems.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Strong attention to detail, scientific thinking, and commitment to data accuracy, ethical AI, and continuous innovation.