Data Analyst

Pope Recruitment Pty; Melbourne; On-site; AUD 80,000 - 110,000; Full time

Job summary

Pope Recruitment Pty is seeking a Data Analyst to analyze large datasets and provide insights to drive business decisions. You will gather data with cross-functional teams, develop reports, and deliver customized solutions to improve performance.

The role emphasizes statistical methods, A/B testing, data quality, and data visualization using Tableau or Power BI, with hands-on work in SQL, R, and Python.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Business Analytics, Statistics or related field.
• 2+ years of relevant experience in data analysis, preferably in the Internet and New Media industry.
• Proven experience in analyzing large and complex datasets using SQL, R, Python, or related tools.
• Experience with data visualization tools such as Tableau, Power BI, or related tools.
• Knowledge of statistical modeling, hypothesis testing, and A/B testing methodologies.
• Familiarity with data management and ETL processes.

Responsibilities

• Analyze large data sets using advanced statistical techniques and tools to uncover trends, opportunities, and insights.
• Develop, maintain and analyze performance metrics and reports that support data-driven decision-making processes.
• Collaborate with stakeholders to identify business questions and translate them into data and analysis requirements.
• Develop models and algorithms to help optimize business processes and drive efficiencies.
• Design and execute A/B tests and experiments to identify opportunities for optimization.
• Identify data quality issues and help to develop solutions to improve data integrity, accuracy, and completeness.
• Manage data collection, cleansing, and manipulation processes to ensure data is readily accessible and easy to work with.
• Prepare and present data-driven reports and insights to stakeholders, highlighting key findings and recommendations.

Skills

Analytical thinking

Communication

Collaboration

Problem-solving

Statistical modeling

Hypothesis testing

A/B testing

Education

Bachelor’s or Master’s degree in Computer Science, Business Analytics, Statistics or related field

Tools

SQL

R

Python

Tableau

Power BI

Job description

Summary:

The Data Analyst will be responsible for analyzing and interpreting large datasets to provide valuable insights and recommendations to the business. They will work closely with cross-functional teams to gather and analyze data, develop reports, and provide customized solutions to help the organization gain a competitive edge.

Responsibilities:

• Analyze large data sets using advanced statistical techniques and tools to uncover trends, opportunities, and insights.


• Develop, maintain and analyze performance metrics and reports that support data-driven decision-making processes.


• Collaborate with stakeholders to identify business questions and translate them into data and analysis requirements.


• Develop models and algorithms to help optimize business processes and drive efficiencies.


• Design and execute A/B tests and experiments to identify opportunities for optimization.


• Identify data quality issues and help to develop solutions to improve data integrity, accuracy, and completeness.


• Manage data collection, cleansing, and manipulation processes to ensure data is readily accessible and easy to work with.


• Prepare and present data-driven reports and insights to stakeholders, highlighting key findings and recommendations.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Business Analytics, Statistics or related field.


• 2+ years of relevant experience in data analysis, preferably in the Internet and New Media industry.


• Proven experience in analyzing large and complex datasets using SQL, R, Python, or related tools.


• Strong analytical, critical thinking, and problem-solving skills.


• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.


• Experience with data visualization tools such as Tableau, Power BI, or related tools.


• Knowledge of statistical modeling, hypothesis testing, and A/B testing methodologies.


• Familiarity with data management and ETL processes.