At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

EY GDS – AI and Data – Data Scientist - Senior Consultant
Preferred Qualifications

• Bachelor’s/master’s degree in mathematics, Computer Science, Engineering, or similar disciplines
• 3-6 years of hands-on Data Science experience with a proven record of successfully deploying projects to production
• Excellent problem-solving and data analysis skills, with expertise in predictive modeling, statistics, data mining, and machine learning algorithms
• Strong Python coding skills and flexibility in other coding languages including R.
• Experience in building powerful visualizations depicting data insights, model performance, and results while leveraging libraries and tools like Plotly, Matplotlib and Power BI
• Demonstrated expertise in working with SQL and other relational databases for data science purposes
• Ability to communicate effectively and manage relationships with stakeholders from both technical and non-technical backgrounds
• Willingness to travel to the Middle East & North Africa (MENA) region based on business needs
• Industry-specific experience in Oil & Gas or Power & Utilities would be preferred.

Responsibilities

• Work independently as well as in a team environment to deliver end-to-end data science projects within the timeline and budget
• Collaborate with business stakeholders to comprehend and translate business problems into well-defined data science projects
• Analyze and interpret complex data sets to identify trends, patterns, and insights thereby creating business value
• Identify machine learning algorithms and methods best suited to solve specific business problems
• Design and conduct experiments to validate hypotheses and test assumptions.
• Effectively communicate findings and recommendations to stakeholders using data visualization tools and techniques
• Build robust code in Python, R, etc for data science applications
• Follow industry best practices, and stay up to date with machine learning research, frameworks, tools, and practices.
   

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