Manager, Marketing Analytics - (Remote - US) - job 1 of 2

As a Manager, Marketing Analytics at Jobgether, you will be responsible for analyzing customer data using SQL and other tools to provide actionable insights. Your duties will also include developing customer segmentation models, tracking key customer metrics like churn and retention, and collaborating with teams to refine marketing strategies. You'll design A/B tests and work with Data Engineering to implement scalable analytics solutions.

To qualify for the Manager, Marketing Analytics position at Jobgether, you should have a bachelor's degree in Statistics, Mathematics, Computer Science, or a related field, along with 5+ years of analytics or customer insights experience in an eCommerce setting. Proficiency in SQL, experience with statistical analysis, and excellent communication skills are essential.

In the Manager, Marketing Analytics role at Jobgether, proficiency in SQL is critical as you'll be analyzing and optimizing complex queries. Additionally, familiarity with various analytics platforms and A/B testing methodologies will enhance your ability to translate data into strategic recommendations.

At Jobgether, the Manager, Marketing Analytics plays a pivotal role in business performance by analyzing customer data to drive strategies aimed at improving customer retention. By understanding key customer metrics and collaborating with various teams, you will provide insights that will significantly influence marketing effectiveness and overall decision-making.

As a Manager, Marketing Analytics at Jobgether, you can expect a competitive salary of $120,000 to $135,000 annually, along with a comprehensive benefits package that includes medical, dental, vision insurance, flexible PTO, 401K matching, wellness programs, and stipends for internet and cell phone usage. You'll also enjoy perks like free lunches on specific days and an annual learning & development stipend.

In responding to this question, share your approach to data analysis, including specific tools like SQL that you use to extract meaningful insights. Discuss how you would segment customer data and what metrics you would focus on to inform marketing strategies.

When answering, highlight your past involvement in designing A/B tests, the metrics you tracked, and how you utilized the results to improve marketing strategies. Mention any specific cases where your tests led to successful outcomes.

Discuss your organizational skills and how you use tools or methodologies to prioritize tasks. Emphasize your ability to remain focused on high-impact projects while maintaining clear communication with stakeholders.

In your answer, identify key metrics such as churn rate, customer lifetime value, and retention rate. Explain why these metrics are significant to marketing analytics and how they can inform strategic decisions.

Here, share a specific instance where your data-driven insights led to action, detailing the steps you took and the resulting benefits for the business. Make sure to quantify your impact if possible.

Discuss your approach to simplifying complex data concepts into relatable and understandable formats. Talk about methods you employ, like visualizations or storytelling techniques, to effectively convey information.

Highlight the importance of cross-functional collaboration in analytics. Explain how teamwork enhances marketing effectiveness and allows for the integration of diverse insights that can lead to better outcomes.

Mention various resources such as industry blogs, webinars, and networking events where you learn about the latest trends and technologies in marketing analytics. Discuss how staying informed helps you apply new insights in your work.

Talk about your openness to feedback and how you view it as a growth opportunity. Share examples of how feedback has led to enhanced analyses or changes in your recommendations.

Describe your familiarity with data visualization tools, discussing how you use them to present insights effectively. Mention any specific tools you've worked with and how they facilitated better understanding of complex data.