Data Scientist

Job Title Data Scientist Location (s) Dubai Years of Experience 5-8yrs Job Description

• Experience of implementing data science based solutions at at enterprise level is mandatory.
• Python,R, TensorFlow, PyTorch, SQL, AWS Cloud Platform, SageMaker, BedRock, Gen AI Frameworks and models,
• Strong traditional Machine Learning experience mandatory,
• Preditive analytics, Classification/Probability algorithms
• Develop a comprehensive data science strategy for the organization by aligning data initiatives with business goals, identifying key data sources, establishing data governance and management practices, implementing advanced analytics and machine learning solutions, and fostering a data-driven culture to drive innovation and decision-making
• Collaborate with business stakeholders to define problem statements, set clear expected outcomes using data science and artificial intelligence, and identify actionable business benefits and opportunities
• Examine extensive datasets to identify significant trends, patterns, and correlations that can provide valuable insights and inform strategic decision-making.
• Apply statistical techniques, data visualization, and analytical tools to uncover underlying relationships and actionable information from complex and voluminous data
• Build and refine predictive models, implement machine learning algorithms, and assess their performance to provide actionable insights and forecasts.
• In model building and evaluation, engineer features and select relevant variables, develop and train predictive models, and then evaluate their performance using appropriate metrics
• Optimize data science workflows to enhance efficiency and continuously improve the accuracy of predictions by streamlining processes, adopting best practices, and iterating on model performance through regular updates and refinements. This involves automating tasks, improving data quality, and implementing advanced techniques to ensure precise and actionable outcomes
• Continuously monitor the performance of deployed models, identifying any degradation in accuracy or relevance and taking necessary steps to retrain or fine-tune them as needed.
• Conduct regular data quality assessments, implementing procedures and tools to ensure the accuracy, completeness, and consistency of data used for analysis and modeling.