Data Analyst - R Programming

at  Randstad

Role Overview: As a Data Visualization Specialist, you will play a crucial role in transforming raw data from various systems and databases into meaningful insights through the creation of visualizations using R and Rmarkdown. Your responsibilities will include data wrangling, visualization creation, and collaborating closely with subject matter experts to ensure accurate and effective data storytelling.

Key Responsibilities:

• Utilize R and Rmarkdown to visualize data flows and processes effectively.
• Wrangle raw data from multiple sources to prepare it for analysis and visualization.
• Collaborate with subject matter experts to understand data requirements and objectives.
• Create visually appealing and insightful data visualizations that effectively communicate key findings.
• Provide support for existing Rmarkdown processes and other data-related activities, especially during the election period.
• Maintain attention to detail and creativity in problem-solving to enhance data visualization techniques and processes.

Requirements:

• Bachelor’s degree in Computer Science, Data Science, Statistics, or related field.
• Proven experience in data wrangling and visualization using R.
• Proficiency in Rmarkdown for creating dynamic reports and presentations.
• Strong attention to detail with the ability to deliver accurate and high-quality work.
• Excellent communication and customer service skills for effective collaboration with team members and stakeholders.
• Ability to work efficiently in a fast-paced environment, especially during critical periods

If you would like to be considered please apply for the role by clicking the apply button or email laura.pierce@randstaddigital.com.au
At Randstad Digital, we are passionate about providing equal employment opportunities and embracing diversity to the benefit of all. We actively encourage applications from any background

• Utilize R and Rmarkdown to visualize data flows and processes effectively.
• Wrangle raw data from multiple sources to prepare it for analysis and visualization.
• Collaborate with subject matter experts to understand data requirements and objectives.
• Create visually appealing and insightful data visualizations that effectively communicate key findings.
• Provide support for existing Rmarkdown processes and other data-related activities, especially during the election period.
• Maintain attention to detail and creativity in problem-solving to enhance data visualization techniques and processes