Business Intelligence Analyst

Team: Product

Location: United States (Remote)

Commitment: Full-time

Workplace Type: remote

Some qualities we think would make you a good fit

• You love a good challenge. You’re bored by a work environment where every day is the same and the steps are all laid out for you. You’d much prefer a variety of challenging work and ownership over the solution, and you like getting to the root of the issue.
• You administer business intelligence with the end user’s needs in mind. You set up tools to maximize value and minimize headaches for the people who use them—sales leaders, product managers, finance partners, and client‑facing teams.
• You love working in a team. You will work in a small but mighty team in charge of the entire data and business intelligence lifecycle, collaborating with our clients, product teams, and go‑to‑market leaders to create a great analytics experience for our users.
• You are both strategic and hands‑on. You’re as comfortable designing an operating model, metrics framework, or forecast as you are writing SQL, building a Tableau dashboard, or debugging a data pipeline.

Key Responsibilities

• 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.

Qualifications

• Experience: 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.
• Strategic & Financial Acumen: Deep fluency in SaaS revenue metrics, forecasting, and financial modeling, with the ability to connect analytics to business strategy and outcomes.
• Data & BI Expertise:
• 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. 
• Technology Stack Experience: 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.
• Programming & Infrastructure Skills: Knowledge of scripting languages such as Python.
• Analytics & Communication: 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.