Generate meaningful insights into our products, operations, and business. Work with management teams to identify and prioritize business questions that can be answered or informed by data analysis. Have an experimentation mindset - create prototypes, iterate on feedback, and move quickly to figure out how to provide useful information to a variety of stakeholders.
Design and deliver compelling dashboards, reports, and visualizations. Use Tableau (or similar tools) to build actionable and understandable visualizations and self‑service reporting that help internal teams and clients improve their operations and make better decisions.
Establish a metrics‑driven culture across the revenue organization. Define core revenue, funnel, and client health metrics; implement governance standards; maintain a regular reporting cadence; and support a culture of clear accountability, performance standards, and continuous improvement.
Build predictive forecasting models and scenario analyses. Develop forward‑looking revenue forecasts, pipeline health views, and risk analyses using integrated data from CRM, finance, and product usage; provide board‑ready insights and clear narratives around performance and outlook.
Serve as a subject matter expert and educator on business intelligence and data‑driven decision making. Educate product and go‑to‑market team members on basic data wrangling, reporting tools, and how to interpret dashboards; stay up to date on data visualization trends and technologies; and closely collaborate with the Grant Street Data Analytics team.
Understand and help maintain high‑quality data pipelines and business intelligence infrastructure.

Requirements

3+ years of progressive experience in Business Intelligence, Analytics, or related roles within a fast‑growing B2B SaaS or technology company, with demonstrated ownership of revenue or product analytics.
Deep fluency in SaaS revenue metrics, forecasting, and financial modeling, with the ability to connect analytics to business strategy and outcomes.
Strong SQL experience and knowledge of data modeling, warehousing, and ETL; ability to combine multiple data sources to create clean datasets for analysis.
Familiarity with business intelligence or data visualization tools such as Tableau, with experience designing dashboards that are both actionable and understandable for non‑technical stakeholders.
Experience developing and interpreting machine learning models.
Expert‑level familiarity with modern go‑to‑market technology ecosystems (CRM, marketing automation, BI/analytics, CPQ), and a proven ability to own and evolve CRM environments such as Salesforce or comparable enterprise platforms.
Knowledge of scripting languages such as Python.
Demonstrated ability to architect analytics platforms, build predictive models, and translate complex data into simple, actionable insights. Exceptional written and verbal communication skills, including experience presenting analysis and recommendations to executive leadership.

Benefits

Minimal travel: typically 2-3 weeks per year for on‑site meetings
Teamwork rewards
Professional excellence acknowledgment
Individual responsibility encouragement
Technology-rich work environment support for on‑site and telecommuting positions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdata modelingdata warehousingETLpredictive forecastingfinancial modelingmachine learningdata analysisdata visualizationdashboard design

Soft Skills

communicationcollaborationeducatorproblem-solvingaccountabilitycontinuous improvementpresentation skillsstakeholder engagementadaptabilitycritical thinking