Data Analyst - job 1 of 5

As a Data Analyst at NIQ, you will be responsible for converting data from contributing retailers and manufacturers into actionable insights, analyzing market data at brand and model levels, and ensuring data quality and timeliness. You'll also be expected to communicate effectively with stakeholders and meet important deadlines.

To apply for the Data Analyst position at NIQ, you should possess intermediate to advanced Excel skills, basic to intermediate programming skills in SQL and Python, and 1-3 years of experience in analytics, data modeling, and visualization. Strong logical thinking, attention to detail, and excellent communication skills are key attributes we are looking for.

The work environment at NIQ is dynamic and fast-paced, ideal for candidates who thrive under pressure. As a Data Analyst, you will be part of a supportive team, with flexible working conditions and opportunities for professional growth, such as LinkedIn Learning and volunteer time off.

Unfortunately, NIQ does not offer visa sponsorship for the Data Analyst position, so it is important that applicants are local citizens or have unrestricted work rights in Australia.

As a Data Analyst at NIQ, you will primarily use advanced Excel, SQL, and Python for data analysis. Familiarity with data visualization tools such as PowerBI and Tableau would be beneficial, though not essential.

When answering this question, highlight specific projects where you've used data visualization tools like PowerBI or Tableau. Discuss how these tools helped convey insights from your analyses, and emphasize your ability to choose the right tool for the specific data set and audience.

Discuss the procedures you follow to verify data accuracy, such as cross-referencing sources, performing data cleansing, and implementing quality control processes. Give examples of past experiences where these methods proved effective.

Provide a clear overview of a specific project, the challenges faced, and the solutions implemented. Focus on your problem-solving skills and how your analytical abilities led to a successful outcome.

Mention your experience with SQL and Python, detailing specific scenarios where these skills were beneficial, such as database queries, automation scripts, or data analysis tasks.

Share your strategies for managing multiple projects, such as using task management tools, setting clear priorities, and maintaining open communication with team members and stakeholders to ensure expectations are aligned.

Discuss metrics relevant to the industry or specific projects you have worked on, demonstrating your understanding of how these metrics inform business decisions and strategy.

Emphasize the importance of open communication and being receptive to feedback. Discuss how you would investigate their concerns, validate your findings, and collaborate with the parties involved to find common ground.

Share a specific case where your data insights led to actionable recommendations. Focus on the impact of your contributions, whether through increased efficiency, revenue growth, or improved customer satisfaction.

Reflect on the aspects of data analysis you find most rewarding, such as problem-solving, uncovering insights, working with cross-functional teams, or the continuous learning the field offers.

Discuss the resources you use to stay updated, such as online courses, workshops, professional networks, or relevant industry publications. Mention specific examples of learning experiences that have contributed to your expertise.