Senior Data Analyst, Commercial Operations

As a Sr. Data Analyst – Commercial Operations, you will be responsible for consolidating, transforming, analyzing, and reporting on revenue and pricing data to help guide business decisions.

This role will utilize SQL (and other data transformation languages) to pull and manipulate data from various data sources, generating insights that answer the critical “Why” behind key performance metrics. The ideal candidate will be passionate about uncovering trends, understanding business dynamics, and providing clear, data-driven insights to the Commercial and Pricing teams.

You will work closely with cross-functional teams to support revenue forecasting and modelling, performance and pipeline monitoring, pricing analysis, and operational optimization, ultimately driving revenue growth.

📍 Location: This is a hybrid role requiring the successful candidate to work three days a week in our Toronto office, located at 351 King Street East, Toronto, ON.

Contact:

Chengeer Lee - Principal Talent Acquisition Partner & Coach

What you will do:

• Collaborate with Revenue Operations and Pricing teams to understand business goals and provide data-driven recommendations to improve pricing strategies, revenue generation, and customer retention.
• Analyze revenue changes, pricing adjustments, and market behaviour through root-cause analysis, identifying areas for optimization across revenue streams and pricing models.
• Develop and maintain models to forecast ARR growth, incorporating customer acquisition, retention, churn, expansion, and pricing adjustments.
• Model various growth initiatives (e.g., new market expansion, pricing structure changes, product development) to evaluate long-term ARR performance.
• Track and forecast license counts and ARR growth across customer segments to ensure alignment with revenue goals and product growth objectives.
• Generate detailed reports and dashboards using SQL to highlight key metrics, such as revenue trends, pricing optimization, sales performance, churn analysis, and customer behaviour.
• Automate and streamline reporting processes to provide timely and actionable insights to leadership and cross-functional teams.
• Perform deep-dive analyses to uncover trends and anomalies, providing actionable insights to drive business performance.
• Ensure data accuracy, consistency, and reliability by auditing and validating data pipelines and sources.
• Collaborate with Product, Sales, Marketing, and Finance teams to ensure data insights align with business objectives and strategic goals.
• Serve as a trusted data partner to senior leadership, delivering clear and concise findings to inform decision-making.
• Prepare and deliver data-driven presentations for Board meetings, executive leadership, and stakeholders, focusing on revenue forecasts, ARR growth, and key performance indicators.

What you will bring:

• Bachelor’s degree in Business, Economics, Data Science, Mathematics, or a related field.
• At least 5+ years of experience in data analysis, with a focus on business, revenue, and pricing analytics.
• Proficiency in SQL (or other data transformation languages) for querying, cleaning, and transforming data within relational databases (e.g., MySQL, PostgreSQL, SQL Server).
• Familiarity with SaaS business models and key metrics such as ARR, Upsell/Downsell, Cross-sell, churn, Win Rate, and Sales Velocity.
• Experience with data visualization tools (e.g., Tableau, Power BI) to create clear and engaging reports and dashboards.
• Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights.
• Proficiency in Python or other scripting languages for advanced data analysis.
• Excellent written and verbal communication skills, with the ability to present data findings to non-technical executive stakeholders.
• This streamlined list maintains the essential details while making the qualifications concise and easy to read. Let me know if any further adjustments are needed!