Head of Analytics

As Head of Analytics, youll lead the analytics team and strengthen how data is used to support decision-making across the company. Reporting to the VP of Data & Analytics, youll translate the broader data strategy into clear priorities, high-quality analytical delivery, and measurable business impact.

Youll manage and develop teams of analysts and BI, partner closely with senior stakeholders across Product, Sales, Marketing, Finance, Customer Success, and Operations, and ensure that the company has trusted metrics, actionable insights, and scalable analytical capabilities.

This is a strategic and hands-on leadership role. Youll be expected to set direction, create structure, raise analytical standards, and remain closely involved in the companys most important business questions.

Youre welcome to work in our offices in Tel Aviv, Israel

Your responsibilities will include:

Team leadership and development. Lead, mentor, and develop the analytics team. Set clear expectations, establish ownership, support professional growth, and create a high-performance culture focused on business impact, analytical quality, and accountability.
Analytics strategy execution. Partner with the VP of Data & Analytics to shape the analytics strategy and own its execution, prioritization, and delivery. Translate company goals into a clear analytics roadmap and ensure resources are focused on the highest-impact business needs.
Business partnership. Act as a trusted analytical partner to senior leaders across Product, Sales, Marketing, Finance, Customer Success, and Operations. Understand their objectives, challenge assumptions, and help turn strategic questions into measurable decisions and actions.
Decision support and advanced analysis. Lead high-impact analyses across customer behavior, product performance, revenue, retention, pipeline, operational efficiency, and business growth. Ensure findings are translated into clear recommendations rather than presented as data alone.
Metrics and analytical governance. Establish and maintain consistent KPI definitions, business logic, and analytical standards. Ensure stakeholders use trusted and aligned metrics across dashboards, reports, forecasts, and business reviews.
Dashboard and reporting oversight. Guide the design, implementation, and improvement of executive and operational dashboards. Ensure reporting is relevant, reliable, easy to use, and aligned with business priorities.
Self-service analytics. Enable business teams to access and use data independently while maintaining appropriate governance, security, quality, and consistency. Identify where self-service creates value and where centralized analytical support is required.
AI-driven analytics. Help define and implement AI-assisted analytics capabilities that reduce manual reporting, accelerate insight generation, support natural-language access to data, and proactively surface risks or anomalies. Establish clear quality and validation standards for AI-generated outputs.
Cross-functional data collaboration. Work closely with Data Engineering, Data Architecture, and other technical teams to ensure that analytical datasets, semantic models, and data pipelines support current and future business requirements.
Operating model and prioritization. Build scalable processes for intake, prioritization, delivery, documentation, and stakeholder communication. Balance urgent business requests with strategic initiatives and long-term capability development.