Sales Analytics Analyst

NinjaOne•Tampa, FL

7d•Hybrid

About The Position

NinjaOne’s continued growth requires increasingly sophisticated insights across the entire customer lifecycle. As we scale, we’re looking for a Sales Analytics Analyst who can turn complex revenue and customer data into clear, actionable insights that help our teams improve retention, adoption, and expansion. In this role, you will focus primarily on our post-sales organization, partnering closely with our post-sales leadership team and CS Operations to build the reporting and analytics that surround the customer lifecycle. You’ll work across Salesforce and other data sources to understand customer health, adoption, renewal risk, retention, and expansion — helping leaders understand not only what is happening in the business, but why. This is a hands-on analytical role for someone who is equally comfortable building the reporting, digging into the data, and communicating what it means. You’ll use Salesforce, SQL, Excel, and BI tools to create scalable reporting, investigate trends, and surface insights that enable better business decisions. Location - Hybrid in Austin, TX or Tampa, FL in the office 3 to 4 days per week (Monday, Tuesday, and Thursday)

Requirements

3+ years of experience in Revenue Analytics, Sales Analytics, Customer Success Analytics, Revenue Operations, Sales Operations, Business Intelligence, or a similar data-focused role; B2B SaaS experience preferred.
Strong Salesforce proficiency, including hands-on experience building and maintaining Salesforce Reports & Dashboards.
Hands-on SQL experience with the ability to query, analyze, and validate business data.
Strong proficiency in Excel and experience using data to investigate business questions and identify meaningful trends.
Experience with Tableau (preferred) or another BI/data visualization platform such as Power BI or Looker.
Strong analytical and problem-solving skills with the curiosity to dig beyond the initial data and understand underlying business drivers.
Strong communication skills with the ability to translate analytical findings into clear insights for non-technical stakeholders.
Understanding of SaaS customer lifecycle metrics such as NDR, GRR, churn, retention, renewal, expansion, and customer health preferred.
Proactive and detail-oriented, with the ability to manage multiple priorities and independently drive assigned work through completion.
Comfortable working in a fast-paced environment with evolving priorities and ambiguity.

Nice To Haves

Experience with Gainsight, Staircase, Python, or other customer analytics/data tools.

Responsibilities

Analyze performance across the post-sales customer lifecycle, including onboarding, adoption, customer health, retention, renewal, and expansion.
Analyze key SaaS metrics including NDR, GRR, logo retention/churn, renewal risk, and expansion to identify trends, drivers, risks, and opportunities.
Investigate changes in business performance to help stakeholders understand what is happening, why it is happening, and where action may be needed.
Support the development and continuous improvement of KPIs and measurement frameworks across the customer lifecycle.
Build and maintain Salesforce Reports & Dashboards for Customer Success Leadership and frontline teams.
Use SQL to query, analyze, and validate business data, investigate trends and anomalies, and perform deeper analysis beyond standard reporting.
Build recurring reporting, analyses, and visualizations using Excel, Tableau, and other BI tools.
Ensure reporting is accurate, consistent, scalable, and provides stakeholders with clear visibility into business performance.
Identify opportunities to automate and scale recurring reporting and analytical processes.
Partner closely with Customer Success Leadership and CS Operations to translate business questions into analytical requirements and actionable insights.
Partner with Analytics, BI, and Sales Systems teams to investigate data discrepancies, improve data quality, and ensure reporting requirements are represented appropriately in systems and datasets.
Communicate analytical findings clearly to technical and non-technical stakeholders, translating complex data into clear business implications and recommendations.
Balance recurring reporting, ad-hoc business questions, and longer-term analytical projects as organizational priorities evolve.
Other duties as needed.