Be a key partner to the executive team on planning, forecasting, and investment tradeoffs — not just reporting on decisions, but helping shape them.
Own the analytical frameworks that inform how RapidSOS allocates resources, evaluates performance, and identifies growth opportunities.
Lead white space analysis, upsell opportunity identification, and customer health scoring to drive GTM strategy.
Influence board and investor narratives by ensuring the data behind our story is airtight, consistent, and compelling.
Establish and enforce definitions for all key business metrics — ARR, churn, pipeline, product utilization, and customer health — across Finance, Revenue, and Product.
Serve as the arbiter of truth when metrics conflict across systems or teams.
Partner with Finance on investor-grade reporting standards and SaaS metric definitions.
Identify opportunities to use AI to automate recurring reporting, anomaly detection, forecasting, and narrative generation.
Build workflows that reduce manual analysis and increase the speed from data to decision.
Partner with Data Engineering and Product to incorporate predictive and AI-generated insights into dashboards and executive reporting.
Establish best practices for responsible AI use in analytics, including validation, governance, and transparency.
Build and maintain dashboards and reporting that drive board, investor, and leadership decisions.
Own the cadence of executive data deliverables including weekly leadership reviews, monthly business reviews, and board packages.
Translate complex data into clear, decision-ready narratives for senior stakeholders.
Embed analytics support across RevOps, Product, and Finance — delivering insights at the speed each team operates.
Partner with Product on utilization metrics, adoption trends, and retention risk signals.
Enable self-serve analytics capabilities across the organization so teams move fast without breaking things.
Hire, develop, and grow a high-impact team of analysts and analytics engineers over time.
Partner closely with the Data Engineering team (Databricks/medallion architecture) to ensure the analytics layer is reliable, scalable, and governed.
Evaluate and evolve the BI and AI toolstack to match the ambition of the function.
Requirements
8+ years in analytics, business intelligence, or data strategy roles, with 3+ years in a leadership capacity.
Deep experience in a B2B SaaS environment — you understand ARR, net revenue retention, CAC, pipeline coverage, and the metrics that matter to investors and operators.
Proven ability to be a strategic partner to senior leadership, not just a reporting function — you’ve influenced planning, budgeting, and investment decisions with data.
Experience using AI tools to accelerate analytics workflows: automated SQL generation, natural language data exploration, AI-assisted modeling, or narrative reporting.
Track record of reducing manual reporting effort through automation or intelligent tooling.
Hands-on with modern BI tooling (Tableau, Looker, Power BI, or similar); strong SQL skills required.
Experience working with cloud data platforms (Databricks, Snowflake, BigQuery, or equivalent).
Executive presence — you can present to the board with confidence and translate complexity into clear decisions.
Comfort experimenting with new tools and shaping how AI is used responsibly inside an organization.
Familiarity with analytics engineering workflows and tools and DataBricks familiarity is a plus.
Prior experience building or formalizing a BI function from the ground up a plus.
Tech Stack
BigQuery
Cloud
SQL
Tableau
Benefits
Competitive salary and benefits and equity participation
A dynamic, flexible and fun start-up work environment with a highly talented team
The chance to work with a passionate team on solving one of the largest challenges globally