Sales Operations Analyst

Job description

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? As a Sales Analytics Analyst, you will join our Sales Operations and GTM Analytics organization, partnering with Sales, Finance, Data Engineering, and Business Systems to make our sales data more reliable, accessible, and actionable. You’ll help build and maintain the data models, reporting, and performance metrics that enable Fin to understand how our sales organization is performing. You’ll also contribute to compensation modeling and reporting, helping ensure that rep attainment and productivity are measured accurately and consistently. This is an opportunity to develop deep expertise in sales analytics while working closely with technical and business partners. We’re looking for someone who is curious, detail-oriented, eager to learn, and excited to use data and AI thoughtfully to solve real operational problems. What will I be doing? Own and maintain foundational sales analytics data models, partnering with Data Engineering to build new models and improve data quality. Build, maintain, and improve recurring reports and dashboards for sales metrics, attainment, productivity, and business performance. Build and support sales compensation models, including the reporting required to track rep performance and attainment. Partner with Finance and Sales Operations to translate compensation plans, business rules, and metric definitions into reliable analytical outputs. Analyze sales performance trends, variances, and data-quality issues to identify risks, opportunities, and areas for improvement. Support reporting and analysis for recurring sales operating cadences, including weekly, monthly, and quarterly business reviews. Work with Data Engineering and Business Systems to define requirements, troubleshoot reporting issues, and test improvements to sales data and systems. Document data definitions, model logic, reporting processes, and assumptions so that stakeholders can confidently use and interpret our metrics. Partner with Sales, Finance, Operations, and Engineering stakeholders to turn ambiguous questions into clear, data-backed recommendations. Use AI tools to accelerate analysis, modeling, documentation, and problem-solving while applying sound judgment and validating outputs before they inform business decisions. Identify opportunities to improve the scalability, accuracy, and efficiency of sales reporting and analytics processes. What skills do I need? 0–2 years of experience in sales analytics, sales operations, business analytics, finance, data analysis, or a related field. A technical or quantitative background and an interest in working with data, systems, and business processes. Basic to intermediate SQL skills, with the ability to query, join, aggregate, and validate data across multiple sources. Experience with Excel or Google Sheets; familiarity with BI or visualization tools such as Tableau, Looker, or Power BI is a plus. Strong attention to detail and a commitment to data accuracy, particularly when working with compensation and performance metrics. Interest in sales performance, forecasting, compensation, productivity, and go-to-market operations. Ability to communicate analytical findings clearly to both technical and non-t