Marketing Data Analyst

As a Marketing Data Analyst at Anteriad, you’ll play a crucial role by liaising between clients and our analytics team, ensuring flawless project execution and supporting various accounts. Your day-to-day tasks will include heavy SQL and Excel work, database analysis, and developing predictive models to help optimize marketing strategies.

To be considered for the Marketing Data Analyst position at Anteriad, you need a quantitative college degree and at least two years of experience in a data analyst role within a corporate environment. Familiarity with SQL is essential, as you will be utilizing it daily, along with possessing strong analytical and communication skills.

As a Marketing Data Analyst at Anteriad, key skills include advanced SQL proficiency, data manipulation capabilities, strong analytical reasoning, and excellent communication skills. Additionally, you should be detail-oriented, able to multi-task, and comfortable working both independently and as part of a team.

The Marketing Data Analyst position at Anteriad offers a hybrid working model, which means you can work remotely, but you'll need to be available to travel to the Rye Brook office intermittently, especially if you are located more than a 45-minute commute from the office.

At Anteriad, Marketing Data Analysts enjoy a comprehensive benefits package, which includes multiple medical plan options, dental and vision coverage, a 401K plan with company match, and generous PTO policies. Additionally, employees benefit from training and development opportunities, community outreach programs, and professional mentoring.

When answering this question, it’s essential to demonstrate your proficiency with SQL. Discuss specific projects where you utilized SQL for data manipulation or analysis, making sure to highlight the techniques you applied and how they contributed to achieving your team's objectives.

In responding to this question, explain your approach to verifying data integrity, such as implementing data validation checks and collaborating with peers to cross-reference findings. Mention using tools and techniques that help monitor accuracy throughout your analysis process.

Describe your time management techniques and how you prioritize tasks. Mention any tools or methods you use to stay organized, like to-do lists or project management software, and emphasize your ability to remain calm and focused under pressure.

Discuss your ability to translate complex data into actionable insights, using visual aids or simplified summaries. Highlight an example where you successfully communicated critical findings to stakeholders who lacked technical expertise, reinforcing your role as a data storyteller.

Share your belief in the value of data-driven marketing, illustrating how it informs strategic decision-making and drives campaign effectiveness. Reference trends or case studies that show the impact of data utilization in achieving marketing goals.

Provide a list of tools and software you've utilized in your data analysis work, such as SQL databases, Excel, or specific analytics platforms. Explain how you've used these tools in past roles to add value to projects and improve outcomes.

When answering this question, describe a specific challenge you encountered, the analytical techniques you employed to overcome it, and the outcome of your efforts. This shows your problem-solving skills and ability to think critically.

Convey your motivation for data analysis by discussing your passion for uncovering insights and contributing to business growth. Consider sharing anecdotes that illustrate how your interests align with the responsibilities of the Marketing Data Analyst role.

Describe the resources you utilize to stay informed, such as industry blogs, webinars, or professional groups. Emphasize your commitment to continuous learning and how you apply new knowledge to your work as a Marketing Data Analyst.

In your response, explain that data storytelling involves conveying insights in a compelling way that resonates with stakeholders. Illustrate your understanding by providing examples from your experience where you transformed data into narratives that drove decisions.