Data Scientist (225-723)

A Data Scientist is an analytical expert who utilizes their skills in both technology and social science to find trends and manage data. They use industry knowledge, contextual understanding, skepticism of existing assumptions – and perhaps most importantly, the ability to interpret data that is both clean and messy – to uncover solutions to business challenges and help make data-driven decisions. Typically, they work with unstructured and structured data that include financial logs, multimedia files, marketing forms, and much more. A Data Scientist helps companies interpret and manage data and solve complex problems using expertise in a variety of data niches, from visualizing data and machine learning to predictive modeling, neural networks, and other advanced analytical techniques. True data-driven decision-making involves not just theory, but also meticulous analysis to drive competitive advantage.

Responsibilities

• Collect, process, and clean data from various sources and devices.
• Analyze massive datasets to identify trends and extract meaningful insights.
• Use machine learning techniques to develop predictive models and algorithms.
• Collaborate with cross-functional teams to define and achieve data objectives.
• Design, develop, and implement complex database models and structures.
• Communicate complex technical information to non-technical stakeholders effectively.
• Create data visualizations to communicate findings to the project team and management.
• Develop and test data mining models and select the most appropriate models.
• Utilize programming languages such as Python, R, and SQL for analysis.
• Stay updated with emerging data science technologies and methodologies.
• Ensure data integrity and security by implementing best practices in data handling.
• Contribute to research processes and development of data-driven solutions.

Requirements

• Bachelor's or Master’s degree in Data Science, Mathematics, or related field.
• Strong proficiency in programming languages such as Python, R, and SQL.
• Experience with machine learning frameworks and data visualization tools.
• Exceptional analytical and problem-solving abilities with attention to detail.
• Excellent verbal and written communication skills are essential for success.
• Proven experience in a data science or analytics role within an organization.
• Ability to work on multiple projects simultaneously and prioritize tasks effectively.