Data Analyst

Roles and responsibilities

Investigate different ranking systems methodologies, criteria, and update the University Ranking Manual regularly.
Collect and manage data from various internal and external sources to ensure accuracy and completeness for analysis.
Assist in the preparation of documentation and data for submissions to ranking organizations.
Develop comprehensive reports and presentations that provide insights into the university's ranking performance, highlighting areas for potential improvement.
Develop and maintain tools and dashboards for ongoing monitoring of KPIs related to university rankings.
Participate in regular meetings, assessing and addressing issues to identify and implement improvements toward efficient operations.
Analyze data related to the university’s international activities, and support the university's internationalization strategy.
Monitor and verify the quality of data and reports to ensure compliance with ranking methodologies and standards.
Regularly follow up with internal departments to monitor progress based on insights from routine reports.
Follow up as appropriate via email, telephone, and/or Zoom.
Data Collection and Management:

Gather and compile data from various sources, ensuring accuracy and completeness.
Maintain databases and data systems, ensuring data integrity and accessibility.
Data Analysis:

Analyze data sets to identify trends, patterns, and insights that can inform business strategies.
Use statistical methods to interpret data and evaluate outcomes.
Data Visualization:

Create visual representations of data (charts, graphs, dashboards) to communicate findings effectively.
Utilize tools such as Tableau, Power BI, or Excel to present data in an understandable format.
Reporting:

Prepare detailed reports summarizing data analysis findings and insights.
Present results to stakeholders and provide recommendations based on analysis.
Collaboration:

Work closely with cross-functional teams (e.g., marketing, finance, operations) to understand data needs and support decision-making.
Collaborate with IT teams to ensure data systems and analytics tools are effectively integrated.
Continuous Improvement:

Identify opportunities for process improvement and recommend solutions based on data insights.
Stay updated on industry trends and best practices in data analysis.
Quality Assurance:

Conduct data validation and quality checks to ensure accuracy and reliability of analysis.
Monitor data for discrepancies and rectify issues as needed.

Desired candidate profile

• Bachelor’s degree in data science, Statistics, Computer Science, or a related field.

Experience:

• Minimum 2 - 3 years of experience in a related field

Skills:

• Familiarity with research principles and terminologies
• High teamwork skills
• Ability to manage a complex workload and work to tight deadlines
• Excellent interpersonal and networking skills
• Proven experience in data analysis and report writing

Experience

• Relevant Experience: 2-4 years of experience in data analysis, data mining, or a related field.
• Industry Experience: Experience in a specific industry (e.g., finance, healthcare, marketing) is desirable.

Skills

• Analytical Skills: Strong ability to analyze complex data sets and derive actionable insights.
• Statistical Knowledge: Proficiency in statistical methods and tools, including hypothesis testing and regression analysis.
• Data Visualization: Experience with visualization tools (e.g., Tableau, Power BI, Matplotlib) to present data effectively.
• Programming Languages: Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis.
• Database Management: Familiarity with database management systems (e.g., MySQL, PostgreSQL) and data warehousing concepts.

Personal Attributes

• Detail-Oriented: High attention to detail to ensure data accuracy and integrity.
• Problem Solver: Strong problem-solving skills to identify trends, patterns, and anomalies in data.
• Curiosity: A natural curiosity and eagerness to explore data and uncover insights.
• Communication Skills: Excellent verbal and written communication skills to convey findings to non-technical stakeholders.

Additional Considerations

• Business Acumen: Understanding of business processes and the ability to translate data insights into strategic recommendations.
• Team Player: Ability to collaborate effectively with cross-functional teams, including IT, marketing, and management.
• Adaptability: Willingness to learn new tools and techniques as the data landscape evolves.