Senior Analyst, Product Analytics

As a Senior Analyst, Product Analytics at Jobber, you will focus on supporting our product development and marketing strategies through detailed data analysis. Your key responsibilities will include proposing analytical solutions, performing hands-on analysis to drive insights, collaborating with the BI and Data Science teams, and helping measure the success of product initiatives.

To be considered for the Senior Analyst, Product Analytics role at Jobber, you should possess expert-level SQL skills, a background in SaaS product analytics, and the ability to work with complex data structures. Additionally, having analytical creativity, business acumen, and strong communication skills will set you apart! A background in Python is also an asset.

Jobber fosters a collaborative and innovative environment for its Senior Analyst, Product Analytics. You will engage in knowledge-sharing sessions, receive support from Development Coaches, and participate in a culture that values inclusivity and growth. This supportive atmosphere minimizes barriers, encouraging you to explore data-driven solutions effectively.

In the Senior Analyst, Product Analytics role at Jobber, you will work on a variety of projects that enhance product functionality and user experience. You’ll collaborate with teams to design experiments, support AI developments, and analyze data to inform business recommendations. Your work will help shape the evolution of Jobber’s products, directly impacting small businesses.

At Jobber, the Senior Analyst, Product Analytics can expect numerous growth opportunities. The company emphasizes talent development with access to resources, coaching, and career path exploration. Working in a fast-paced environment allows you to hone your analytical skills while taking on new challenges and responsibilities to advance your career in the analytics field.

In preparing your answer, share specific projects where you've utilized SQL to manipulate large datasets and derive meaningful insights. Highlight your understanding of complex relational data structures and how your SQL expertise has contributed to product development decisions in the past.

Discuss your strategy for understanding stakeholder objectives and how you translate those into analytical proposals. Provide examples of previous collaborations and how you ensured stakeholder alignment and buy-in to your data-driven recommendations.

Detail the analytical techniques you employ, such as A/B testing, regression analysis, or cohort analysis. Share examples of how you've previously measured the impact of product initiatives using these methodologies and any metrics that were particularly telling.

Articulate your methods for keeping up with industry trends, like following leading analytics blogs, engaging in online courses, or participating in webinars. Mention community involvement, such as meetups or forums, which help you gain insights from fellow industry professionals.

Share a specific example of a challenging situation where you had to dig deep into data to find a solution. Explain your thought process, the tools you used, and how the outcome improved either a product or a business decision.

Discuss your methodology for aligning analytical projects with broader business goals. Reference your experience in translating business needs into specific, measurable KPIs to guide your work and ensure that your insights support key decision-making.

When discussing a successful insight, focus on the context, the analysis you conducted, the insights derived, and the actions taken by the business as a result of your recommendations. Emphasize the positive impact of your work on the team or company.

Explain how analytical creativity allows you to look for unique solutions or patterns in data that may not be immediately obvious. Share examples where innovative thinking led to valuable insights or the development of new analytics processes.

Illustrate your prioritization process, perhaps by discussing your methods for assessing task urgency and importance. Share an example of a time you successfully managed competing deadlines or shifting priorities in a previous role.

Describe your techniques for distilling complex analyses into clear, understandable formats for your audience. Mention your experience creating visual data presentations, tailored reports, or utilizing storytelling techniques to make data relatable.