Intern, Data Analytics

Job Responsibilities:

Data Collection and Validation

• Assist in gathering data from various internal systems such as Property Management Systems (PMS), customer feedback platforms, and financial databases. Ensure data accuracy and completeness through routine validation and cleansing processes.

Data Preparation and Transformation

• Perform data preprocessing tasks including cleaning, formatting, and structuring datasets to prepare them for analysis and reporting. This may involve handling missing values, standardizing formats, and merging multiple data sources.

Report and Dashboard Support

• Collaborate with senior analysts to update and maintain operational and management dashboards using tools like Power BI or Tableau. Ensure timely refresh of data and troubleshoot any discrepancies in visualizations.

Basic Data Analysis and Insights Generation

• Conduct preliminary exploratory data analysis to identify trends, patterns, and anomalies. Support the team by producing summary statistics and simple visualizations to aid business decision-making.

Documentation and Process Improvement

• Document data workflows, processing steps, and standard operating procedures to enhance team knowledge sharing and operational consistency. Propose suggestions for process automation or efficiency improvements where applicable.

Cross-Functional Collaboration

• Work closely with stakeholders from operations, marketing, and revenue management teams to understand data requirements and support specific analytics requests or ad hoc reporting needs.

Learning and Skill Development

• Continuously develop technical skills in data analytics tools (such as PowerBI), programming languages (such as Python or SQL), and domain knowledge in hospitality analytics, contributing actively to team knowledge exchange sessions.

Job Requirements:

• Currently pursuing a degree in Business Analytics, Data Analytics, Data Science, Computer Science, Information Systems, Engineering (with data-related coursework)or related studies in Analytics.
• Academic exposure to data query languages like SQL and Python.
• Familiar with dashboard visualization tools like PowerBI, Tableau, QlikView.