Data Scientist
Mashreq
Total years of experience :7 years, 0 Months
EXPERIENCE
Mashreq
Data Scientist & Analystic 09/2021 - 11/2023 Dubai
Strong programming skills, particularly in Python and/or Data Robot platforms. Proficiency in SQL, Map/Reduce, Hadoop and database management. Knowledge of additional programming languages is a plus (C++, Java, SPSS, SAS, Scala). Knowledge of statistical modelling and machine learning algorithms. Experience with data visualization tools, such as Tableau or Power BI. Ability to work with large, complex datasets. Familiarity with cloud platforms and big data technologies. Solid understanding of data pre-processing (using Databricks), feature engineering, and model evaluation techniques. Experience working with Azure services and platforms such as Azure ML, Azure Databricks, Azure fundamentals and Azure dev-ops. Design, develop, and deploy predictive models to identify suspicious stock trading and potentially fraudulent activities. Generate daily, weekly, and monthly reports that highlight potential risk areas and provide actionable insights. Present findings and insights to senior management, informing decision-making processes. Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence techniques, and provide technical leadership and guidance to the team. Develop dimensions of the DS project such as data analysis, visualization and development of tools, models and documentation. Analyze business metrics and KPIs to understand trends, identify issues, and opportunities for optimization. Clean, transform, and structure raw data to make it usable for analysis and reporting. Design and manage data storage solutions, ensuring scalability and performance. Ensure data integrity, quality, and compliance with relevant regulations and standards, implementing best practices for data governance and security. Collaborate with data analysts and data scientists to create insightful reports and visualizations. Support the development of predictive models and analytics solutions. Continuously monitor and optimize data pipelines and infrastructure for efficiency and reliability. Troubleshoot and resolve data-related issues promptly. Collaborate cross-functionally with business stakeholders, data engineers, and IT teams to integrate data science solutions into business processes and systems, and effectively communicate insights and recommendations to non-technical audiences. Conduct exploratory data analysis, develop predictive models, and apply machine learning algorithms to extract insights, solve complex problems, and drive actionable recommendations.
Strong programming skills, particularly in Python and/or Data Robot platforms. Proficiency in SQL, Map/Reduce, Hadoop and database management. Knowledge of additional programming languages is a plus (C++, Java, SPSS, SAS, Scala). Knowledge of statistical modelling and machine learning algorithms. Experience with data visualization tools, such as Tableau or Power BI. Ability to work with large, complex datasets. Familiarity with cloud platforms and big data technologies. Solid understanding of data pre-processing (using Databricks), feature engineering, and model evaluation techniques. Experience working with Azure services and platforms such as Azure ML, Azure Databricks, Azure fundamentals and Azure dev-ops. Design, develop, and deploy predictive models to identify suspicious stock trading and potentially fraudulent activities. Generate daily, weekly, and monthly reports that highlight potential risk areas and provide actionable insights. Present findings and insights to senior management, informing decision-making processes.
Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence techniques, and provide technical leadership and guidance to the team. Develop dimensions of the DS project such as data analysis, visualization and development of tools, models and documentation. Analyze business metrics and KPIs to understand trends, identify issues, and opportunities for optimization. Clean, transform, and structure raw data to make it usable for analysis and reporting. Design and manage data storage solutions, ensuring scalability and performance. Ensure data integrity, quality, and compliance with relevant regulations and standards, implementing best practices for data governance and security. Collaborate with data analysts and data scientists to create insightful reports and visualizations. Support the development of predictive models and analytics solutions. Continuously monitor and optimize data pipelines and infrastructure for efficiency and reliability. Troubleshoot and resolve data-related issues promptly. Collaborate cross-functionally with business stakeholders, data engineers, and IT teams to integrate data science solutions into business processes and systems, and effectively communicate insights and recommendations to non-technical audiences. Conduct exploratory data analysis, develop predictive models, and apply machine learning algorithms to extract insights, solve complex problems, and drive actionable recommendations.