Senior Manager, Analytics and Insight (Hybrid)

Senior Manager, Analytics and Insight (Hybrid - 2 days onsite per week) 

Overview:

As the Senior Manager of Analytics & Insights, you will lead the team responsible for transforming data into trusted, actionable intelligence and data-driven strategic recommendations for teams across the organization. You will manage a cross-functional team of analysts and data scientists, driving the shift from reactive reporting to proactive, strategic insight generation. This role sits within the Data organization, reporting to the VP of Data, and serves as a critical bridge between technical data infrastructure and business decision-making. Success looks like a team that operates with high autonomy, delivers consistent metric integrity,  enables self-service analytics at scale, and serves as trusted thought partners for leaders throughout the business.

The impact you'll make:

• Define and execute the analytics strategy across BI, analytics, and data science functions to align with company OKRs and CTO-level priorities
• Own the organization's metrics framework, ensuring consistency, accuracy, and trustworthiness of KPIs across all business domains
• Lead the build-out of self-service analytics capabilities, including dashboard infrastructure, semantic layers, and AI-powered tooling
• Drive proactive strategic insights to improve the caliber of decision-making across the business
• Partner with Engineering, Product, Finance, and Marketing stakeholders to prioritize data workstreams and translate business questions into scalable analytical solutions and recommendations
• Identify and execute opportunities to improve team efficiency through tooling, AI integration, and cross-functional process improvement
• Oversee analytics support for critical business initiatives including ERP migrations, compliance workstreams, and platform transitions
• Present strategic findings, metric insights, and team roadmap to executive leadership and the CTO
• Design and oversee A/B testing and other experimental methodologies to validate product hypotheses
• Stay current with industry trends and best practices in analytics

What you've accomplished:

• Lead and develop an 6+ person team spanning analytics, business intelligence, and data science
• Own hiring, onboarding (including structured 30/60/90 plans), performance management, and career development for all direct reports
• Foster a culture of ownership, intellectual rigor, and continuous improvement, including deliberate upskilling in AI-assisted workflows
• Triage and prioritize team backlog in partnership with stakeholders, balancing strategic initiatives against ad hoc demand
• Bachelor’s degree in Business, Data Science, Statistics, or a related field; Master’s degree preferred.
• 8+ years of experience in product analytics, business intelligence, or a related field, with 3+ years in a management role.
• Strong SQL proficiency and hands-on familiarity with cloud data warehouses (e.g., Snowflake) and transformation frameworks (e.g., dbt)
• Experience managing mixed-discipline teams including analysts, data scientists, and/or BI engineers
• Demonstrated ability to drive metric standardization, data governance, and self-service infrastructure at scale
• Strong executive communication skills with a track record of influencing decisions at the VP/C-suite level
• Proficiency in data analysis tools (e.g., SQL, Python) and visualization platforms (e.g., Sigma, Tableau)
• Strong understanding of statistical methods, A/B testing, and user research techniques
• Proven ability to manage projects effectively and work collaboratively in a fast-paced environment

Bonus points: 

• Experience with Sigma, Tableau, or comparable BI platforms, particularly in a migration or platform consolidation context
• Familiarity with AI/LLM tooling applied to analytics workflows, documentation, or operational efficiency
• Background in ecommerce, marketplace, or regulated industries (cannabis, pharma, fintech)
• Experience supporting SOX-adjacent data validation or ERP integration workstreams
• Exposure to product analytics, experimentation framework