Product Analytics Manager

Jobber•Toronto, ON

62d•$121,000 - $163,600•Onsite

About The Position

Are you passionate about using data to drive impactful product decisions? Then Jobber might be the place for you! We’re looking for a Product Analytics Manager to be part of our Strategy & Analytics team. Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want! Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish for our customers. The Team: Product Analytics is part of the Analytics & Strategy department, our internal consulting team – they’re the decision support mechanism that connects data, business insights and an internal tech stack (systems) with the rest of the organization. In essence, Product Analytics is a central function that exists to drive business outcomes in all corners of Jobber’s ecosystem. The team is embedded in product development and works closely with Product, Design, Engineering, and GTM stakeholders to make sure every major decision has the analytical foundation it deserves. We're a collaborative, curious group. We debate methods, share what we're learning, and take the work seriously without taking ourselves too seriously. The people who thrive here are the ones who want to understand why something works, not just report that it did. The Role: Reporting to the Director of Product Analytics, the Product Analytics Manager will champion analytical initiatives designed to advance Jobber’ subscription product capabilities (desktop & Mobile App), user experience and product marketing strategy. The purpose of the role is to ensure that Product Development, Experimentation and Product Marketing teams have all the information they need to make design, experience and GTM decisions that drive success of the Jobber product in the market, as well as measure the success of those initiatives. This is a high impact, hands-on individual contributor role. What you will do is own a product domain analytically, from the framing of the question through to the recommendation that lands in a product or GTM decision.

Requirements

Deep, hands-on experience in product analytics for a SaaS or marketplace product you've worked in a product development cycle, not just reported on outcomes after the fact
End-to-end experimentation experience: you've designed the test, chosen the metrics, monitored for novelty effects, handled early-stopping decisions, and communicated the results to a non-technical audience
Fluency with causal inference - you understand when an A/B test isn't possible or appropriate, and you have a toolkit for those situations
Strong analytical SQL: complex joins, window functions, cohort analysis, funnel construction; you write it to think, not just to pull data
The ability to simplify without losing accuracy, you can take a technically complex result and give a stakeholder exactly what they need to make a decision, nothing more
Comfort with uncertainty: you communicate confidence intervals, flag where signal is thin, and push back on requests for false precision
Python for analysis and modeling, pandas, statsmodels, scikit-learn
To have a strong and confident communication style. You have the ability to actively listen, empathize and consult with stakeholders, and you can take something complex and difficult and make it easy to digest.
Be comfortable in an ambiguous and fast-paced environment. We’re growing fast and things are changing every day – what worked yesterday might not anymore.

Nice To Haves

Bayesian methods or probabilistic modeling for situations where frequentist approaches don't fit
Experience with Monte Carlo simulation or scenario modeling for business planning problems
Informal leadership experience, mentoring peers, running knowledge-sharing sessions, helping junior analysts level up, even without a formal title
Be curious and relentless. You are comfortable seeking information independently, solving conceptual problems, corralling resources and delivering results.

Responsibilities

Design, run, and analyze experiments; including navigating the real constraints of a SaaS environment: low traffic, small samples, multiple concurrent product changes, and the temptation to call significance too early
Apply causal inference methods where clean A/B testing isn't possible; difference-in-differences, regression discontinuity, synthetic controls, CUPED/variance reduction techniques
Build customer segmentation and lifecycle models that feed directly into product and GTM decisions, not just sit in a dashboard
Partner with Product, Design, and GTM stakeholders to translate ambiguous business questions into analytical plans; and push back when the question itself needs reframing
Develop scenario and sensitivity models that let business leaders stress-test assumptions before committing to a strategy
Contribute to Jobber's experimentation culture by consulting on experimental design, statistical best practices, and measurement frameworks across teams
Work with Analytics Engineering to define data requirements and ensure the instrumentation exists to answer the questions that matter
Support experimentation initiatives by providing requirements for experimental design and successful measurement and Jobber’s general culture of experimentation by providing consultation on best practices (e.g. applied statistics, tooling, quantity of experiments, importance statistical significance).
Foster a collaborative and supportive work environment by actively participating in knowledge-sharing sessions and seizing opportunities to mentor and guide peers, contributing to the professional growth and development of the team.

Benefits

A total compensation package that includes an extended health benefits package with fully paid premiums for both body and mind, matching in RRSP, TFSA or FHSA, and stock options.
A dedicated Talent Development team and access to coaching, learning, and leadership programs to help you grow your career, reach your goals, and unlock your full potential.
To work with a group of people who are humble, supportive, and give a sht about our customers.
We believe that diverse teams perform better and that fostering an inclusive work environment is a key part of growing a successful team. We welcome people of diverse backgrounds, experiences, and perspectives. We are an equal opportunity employer, and we are committed to working with applicants requesting accommodation at any stage of the hiring process.

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