Who You Will Be Joining:
We are looking for a Sr. Product Analyst to join our Data Science Team in building and expanding our product analytics capabilities at ecobee. This newly established team of product-focused data scientists will derive both customer and financial insights to improve decision making for our products lines, while building automated reporting for our key performance metrics.
We have recently started building this function so there is an opportunity for you to make an impact. The team owns the building and maintaining product analytics infrastructure and partners closely with product stakeholders to understand their growing analytical needs. It defines and builds product success metrics, provides key insights of performance drivers and user behavior, and designs and runs experiments to understand user behaviour.
The ideal candidate brings analytical rigor, experience in identifying gaps and improving product analytics capabilities. You have an opportunity to influence leadership with data and clearly articulate and execute top priorities.
How you’ll make an impact:
- Work closely with product stakeholders to find answers to strategic business questions, as well as surface insights and identify new questions that are critical to understand the business and user behavior
- Own the building and maintaining of infrastructure used to conduct experiments aimed at supporting product functions. You will partner with product stakeholders on the experiment design, implementation, recommendations for the future and post-launch analysis steps
- Create consistency in data reporting and measurement across the board, collaborating with both product stakeholders and our BI team. In addition, the product analytics team will identify automation opportunities and build the tools and processes that streamline recurring reporting to meet our team's analytical needs
- Combine a deep understanding of the business with technical expertise, act as a SME to provide insights to critical product/business questions and tell the story of what happened and why it happened
- Support product teams in making informed decisions by providing data-driven recommendations
- Cultivate knowledge, establish best practices, and disseminate them across various teams
What You’ll Bring to the Table:
- You bring a well-balanced mix of experience including a history of experiment design/execution, deep analytics, data engineering, stakeholder management and product strategy
- Experience implementing/developing product analytics frameworks, techniques and reporting that deliver user insights, guide product decisions, and measure product performance
- Experience with data visualization tools (Looker, Tableau, SiSense), user experience tools (Google Analytics, Amplitude, Segment, MixPanel) and with data extraction, statistical analysis, modeling and general familiarity with data languages and statistical tools (SQL, Python, R)
- Experience working in experiment-driven product development. You are familiar with the different types of experimentation frameworks that impact product decisions. (Including but not limited to A/B testing, principles of causal inference, and statistical techniques like model-based evaluations of user behaviour)
- Strong storytelling skills in presenting complex findings in an easily digestible way in order to influence business change based on derived insights
- Experience in working with stakeholders with various degrees of technical expertise
- You will work with teams across multiple time zones
Just so you know: The hired candidate will be required to complete a background check.
What happens after you apply:
Application review. It will happen. By an actual person in Talent Acquisition. We get upwards of 100+ applications for some roles, it can take a few days, but every applicant can expect a note regarding their application status.
Interview Process: 3 rounds with a take-home challenge
- Round 1: A 45-minute phone call with a member of Talent Acquisition
- A Take-Home Challenge: To be completed over the course of a week and submitted for review.
- Round 2: A 45-minute virtual interview with the Technical Lead of the Product Analytics team.
- Round 3: A 1-hour virtual interview with members of our Product Management team, and our VP of Data Science.