Senior Manager of Analytics, LeanTaaS

• Bachelor's degree in a STEM field or equivalent years of related experience
• 5+ years of experience in product analytics, data science, or a related field, ideally within a SaaS or healthcare technology environment
• People management experience and skills
• Strong experience managing analytics teams or cross-functional data initiatives
• Proficiency with SQL and modern analytics tools (e.g., Looker, Tableau, Power BI, or similar)
• Demonstrated success in using data to inform product decisions, measure impact, and drive customer value
• Strong project management skills and the ability to prioritize work across multiple stakeholders

Desirable

• We are seeking a strategic and hands-on leader to lead our data analytics initiatives and capabilities for our perioperative SaaS product.
• This role will oversee a team of data analysts, manage key analytics platforms, support product innovation through data insights, and enable customer outcomes through scalable analytics delivery
• Lead, coach, and mentor a growing team of analytics professionals
• Champion high data quality standards and foster a strong data-driven culture
• Build the infrastructure and team practices needed to support scale and operational excellence
• Define and evolve how product performance, user behavior, and configuration data are measured and acted upon
• Partner with Product, Engineering, and Design to bring analytical rigor to product development and prioritization
• Translate product usage insights into business outcomes and customer value
• Drive exploration and early validation of new product ideas through data
• Inform product strategy by identifying patterns and opportunities across customers and markets
• Collaborate cross-functionally to evaluate experiments and iterate on promising concepts
• Own the vision for analytics that serve both internal teams and customers
• Work across the organization to define key metrics and build scalable approaches to delivering insights
• Continuously improve how analytics are delivered, consumed, and acted upon