Data Analyst 2 - Clienteling - HYBRID

As a Data Analyst 2 at Nordstrom, your key responsibilities include collecting and analyzing data to enhance customer experience outreach, operationalizing accurate data lists for marketing compliance, and providing monthly data analysis on outreach outcomes. You'll also partner with various stakeholders to create effective outreach strategies and ensure accurate measurements and reporting of customer data.

To qualify for the Data Analyst 2 role at Nordstrom, you should possess a quantitative degree (preferably a Master's) in fields like mathematics, statistics, or computer science. Additionally, at least one year of corporate experience in data analysis, SQL querying, and programming in R or Python is required. Understanding of statistics and good communication skills are also essential for conveying your findings effectively.

Nordstrom values its employees as its most important asset and provides a comprehensive benefits package for Data Analyst 2 positions, including medical, dental, vision plans, retirement options, life insurance, and paid time off. Additionally, employees enjoy a merchandise discount, and access to various resources that promote overall well-being.

Succeeding as a Data Analyst 2 at Nordstrom requires strong analytical skills, proficiency in SQL, and experience with statistical analysis tools like R or Python. Additionally, having a customer-focused mindset, the ability to communicate complex data simply, and a commitment to professionalism and initiative are crucial for driving results and building trust within the team.

The Data Analyst 2 position at Nordstrom is hybrid, offering flexible work options that include both in-office and remote work. This arrangement allows you to balance your professional responsibilities with personal commitments while still engaging closely with your team and contributing to our customer experience initiatives.

In your answer, focus on specific projects where you've written SQL queries to extract and analyze data sets. Highlight your ability to manipulate large databases, ensure data accuracy, and generate reports that influenced business decisions. Providing context about the impact of your work can demonstrate your effectiveness.

Discuss the statistical methods you frequently use, such as regression analysis or A/B testing. Explain why you prefer them based on their efficiency in providing insights, enhancing decision-making, and how they helped solve specific problems in previous roles, particularly in retail data analytics.

Describe your process for verifying data accuracy, such as implementing checks and balances or utilizing software tools for validation. Stress the importance of this integrity for decision-making and how it impacts overall client outreach strategies.

Share a specific example where you simplified a complex data set into understandable insights tailored for non-technical stakeholders. Emphasize your approach to data visualization techniques and how your findings influenced strategic decisions in your past role.

Discuss specific projects where you used R or Python for data analysis. Highlight your familiarity with libraries and functions that aided in your analysis, and how these tools helped you deliver actionable insights effectively.

Describe your time management strategies and organizational skills. Provide examples of how you prioritized tasks, and maintained productivity under pressure, ensuring that all projects were completed accurately and timely.

Explain the critical role communication plays in conveying complex data insights to various stakeholders. Discuss how tailoring your communication style based on audience knowledge levels can drive better decision-making and foster collaboration.

Discuss how integrating customer feedback helps refine outreach strategies, improve customer experience, and how you analyze trends from feedback to inform business decisions. Use examples to illustrate your approach.

Outline the tools and techniques you embrace for data visualization, like Tableau or Power BI. Explain why effective visualization is crucial for presenting data insights clearly, making them more accessible to business stakeholders.

Share your passion for data analytics and customer experience with a specific focus on why Nordstrom's values align with your career ambitions. Highlight any personal connections to retail or experiences that make this role particularly appealing to you.