Senior Commercial Data Analyst

LRN is the world’s leading dedicated ethics and compliance SaaS company, helping more than 30 million people every year navigate complex regional and global regulatory environments and build ethical, responsible cultures. With over 3,000 clients across the US, EMEA, APAC, and Latin America—including some of the world’s most respected and successful brands—we’re proud to be the long-term partner trusted to reduce organizational risk and drive principled performance. 

Named one of Inc Magazine’s 5000 Fastest-Growing Companies, LRN is redefining how organizations turn values into action. Our state-of-the-art platform combines intuitive design, mobile accessibility, robust analytics, and industry benchmarking—enabling organizations to create, manage, deliver, and audit ethics and compliance programs with confidence. Backed by a unique blend of technology, education, and expert advisement, LRN helps companies turn their values into real-world behaviors and leadership practices that deliver lasting competitive advantage. 

We are seeking a commercially minded Senior Commercial Data Analyst to help LRN turn complex data into clear, actionable business insights. This role will support decision-making across pricing, go-to-market strategy, revenue performance, customer retention, and commercial planning.

You will independently structure and analyze data from multiple sources, identify the commercial drivers behind performance, and translate your findings into practical recommendations for senior stakeholders. You will play a central role in strengthening LRN’s commercial reporting, pricing governance, win/loss analysis, and understanding of revenue growth.

This is a hands-on individual-contributor role requiring both technical analytical capability and strong commercial judgment. The successful candidate will be comfortable working with ambiguity, challenging the quality or interpretation of data, and determining the most effective analytical approach without relying on highly prescriptive direction.

You will partner closely with Commercial Strategy, Sales, Client Success, Finance, Product, and Revenue Operations in a fast-paced and evolving global environment.

• Commercial Performance: Providing visibility into ARR, pipeline, new business, expansion, retention, and churn performance
• Pricing and Price-Book Management: Analyzing and maintaining pricing structures to support accuracy, consistency, competitiveness, and governance
• Win/Loss Analysis: Identifying the factors influencing deal outcomes and converting findings into actionable recommendations
• Commercial Insights: Translating complex data into clear conclusions, business implications, and recommended actions
• Reporting and Data Quality: Improving the reliability, consistency, and usability of commercial data, dashboards, and reporting processes
• Strategic Analysis: Supporting product launches, market assessments, segmentation, and other priority commercial initiatives

• Bachelor’s degree in Economics, Mathematics, Statistics, Business, Finance, Computer Science, Data Analytics, or another relevant field required
• Relevant certifications in tools or methodologies such as Salesforce, Domo, Power BI, Alteryx, Excel, or SQL are preferred
• Familiarity with AI tools such as ChatGPT or Copilot for analysis, research, and workflow efficiency is advantageous
• Demonstrated ability to use emerging technologies responsibly while maintaining data security, accuracy, and critical judgment

• Independently structure and analyze complex commercial questions, identifying the appropriate data, methodology, assumptions, and level of analysis
• Analyze ARR, revenue, pipeline, bookings, pricing, customer, and product data to identify trends, performance drivers, risks, and opportunities
• Evaluate performance across new business, renewals, upsell, cross-sell, contraction, and churn
• Segment findings by relevant dimensions such as geography, customer size, product, industry, sales team, deal type, and customer lifecycle stage
• Translate analytical findings into concise, evidence-based recommendations for commercial and senior leadership
• Clearly distinguish between confirmed findings, reasonable assumptions, and areas where additional data is required
• Develop a strong understanding of LRN’s commercial model, products, customers, and core SaaS performance metrics

• Own recurring price-book analysis and support the maintenance and governance of pricing structures
• Analyze list prices, realized prices, discounting, contract terms, product mix, and deal size
• Identify pricing inconsistencies, margin risks, discounting trends, and opportunities to improve commercial outcomes
• Support pricing reviews, product launches, packaging decisions, and market assessments
• Partner with Sales, Finance, Product, and Revenue Operations to improve pricing data and reporting

• Develop structured win/loss analysis to identify the factors influencing deal outcomes, including pricing, product fit, competition, customer needs, and sales execution
• Analyze customer retention, renewal, expansion, contraction, and churn patterns
• Combine commercial, customer, and product-usage information to identify potential retention risks and growth opportunities
• Recommend actions based on findings and monitor whether implemented actions improve performance

• Develop and maintain dashboards and recurring reporting using Salesforce, Domo, Excel, and other business intelligence tools
• Validate data before conducting analysis and proactively identify inconsistencies, gaps, or limitations
• Establish clear definitions and repeatable methodologies for key commercial metrics
• Improve the consistency, accuracy, and usability of commercial reporting
• Automate and streamline recurring reporting and analytical processes
• Document data sources, calculations, assumptions, and reporting methodologies

• Partner with Commercial Strategy, Sales, Client Success, Finance, Product, and Revenue Operations on ongoing and ad hoc initiatives
• Clarify stakeholder questions and convert broad business needs into structured analytical work
• Present findings and recommendations clearly to technical and non-technical audiences
• Contribute to leadership presentations, commercial reviews, and strategic planning materials
• Manage multiple priorities while communicating trade-offs, risks, and timelines

• Five or more years of experience in commercial analytics, data analytics, business analytics, revenue operations, sales operations, pricing analytics, or a related field
• Demonstrated experience analyzing commercial, sales, revenue, or customer-performance data
• Practical experience in at least two of the following areas: pricing, pipeline, win/loss, new business, customer retention, churn, renewal, or expansion analysis
• Experience working in a SaaS, technology, subscription, or similarly data-driven environment strongly preferred
• Understanding of recurring-revenue metrics such as ARR, retention, churn, expansion, and pipeline conversion preferred

• Advanced Excel skills, including complex formulas, PivotTables, data transformation, and analytical modelling
• Strong working knowledge of SQL and experience manipulating data from multiple sources
• Experience using Salesforce data for commercial or performance analysis
• Experience developing dashboards and reporting in Domo, Power BI, Tableau, or a comparable business intelligence platform
• Experience with Alteryx, Power Query, Python, or another data-transformation or automation tool is advantageous
• Strong understanding of data validation, reporting accuracy, and analytical methodology

• Strong commercial judgment and the ability to connect analytical findings to business performance
• Able to work independently, structure ambiguous problems, and determine the appropriate analytical approach
• Comfortable challenging data quality, assumptions, and existing interpretations when appropriate
• Curious, proactive, and motivated to understand the reasons behind performance—not simply report results
• Able to prioritize the most meaningful insights rather than presenting every available data point
• Comfortable operating in a fast-paced environment with evolving priorities

• Able to translate complex analysis into clear, concise, and actionable business recommendations
• Strong written, verbal, and presentation skills
• Comfortable presenting findings, explaining assumptions, and responding to questions from senior stakeholders
• Able to tailor communication for both technical and non-technical audiences