Senior Manager, Risk Analytics

Demonstrable experience as a people leader in analytics. Deep expertise in the Risk domain and Risk analytics. Executive presence and a business mindset. Expert-level SQL skills. Experience with Python and data modeling are strong assets. Familiarity with BI and data visualization tools such as Tableau. Demonstrated expertise in foundational and advanced analytics techniques. Strong business acumen and a strategic mindset. Passion for storytelling through data. Exceptional communication and stakeholder management skills. Proactive and forward-looking mindset. Intellectual curiosity, creativity, and adaptability. Proven ability to thrive under pressure, maintaining focus and delivering clarity amid ambiguity. Solid understanding of SaaS business models, customer health metrics, and operational levers. Comfortable with a high degree of ambiguity and autonomy. Familiarity with Stripe data and payment orchestration systems. Familiarity with Fraud prevention tooling and data. Familiarity with discounted cash flow frameworks for risk decisioning. Ability to foster a collaborative and supportive work environment. Proactive and resourceful, with a bias for action.

Lead and develop a high-performing team of analysts. Organize, mentor, empower, and scale a team of analysts. Prioritize, scope, and allocate analytics work based on business impact and stakeholder needs. Create a collaborative and high-accountability environment. Develop talent through mentorship and feedback. Model analytical leadership. Act as a strategic thought partner and internal consultant to the Risk Org. Provide analytical perspectives that inform business strategy and operational priorities. Anticipate business needs and proactively identify analytical opportunities. Frame complex business challenges into structured analytical approaches. Leverage advanced analytics to elevate Jobber’s analytical capabilities. Collaborate with BI and Data Science on initiatives. Champion analytical best practices. Manage large-scale analytics pipelines. Promote strong analytical foundations through consistent metric design and data quality standards. Build compelling, executive-ready narratives. Enable scalable self-serve analytics.