Business Analyst II

Sourcebooks•Naperville, IL

2d•$105,000 - $125,000

About The Position

Sourcebooks is seeking a Business Analyst II to partner with Sales, E-commerce, Finance, Marketing, and Publishing teams on questions that shape publishing performance. The role translates business questions into reporting, forecasts, and analytical tools, and collaborates with colleagues across Sourcebooks to interpret results and apply insights. Reporting to the Senior Director of Analytics, the Business Analyst II owns select analytical products from development through ongoing operation. Initial work includes forecasting, retailer reporting, and advertising analytics, in collaboration with Power BI and data engineering colleagues. The role also applies AI-assisted and programmatic approaches to make analytical work more useful, reliable, and efficient. The position can be hybrid or remote in New York or Naperville, Illinois, or remote from specified states. It is an exempt salaried position with an annual salary range of $72,000–$78,000. Starting pay is determined based on job-related factors, including geographic location, market conditions, relevant experience, training, and education.

Requirements

A proactive approach, a can-do spirit, and a willingness and ability to grow and learn.
Demonstrated experience building reports and analytical tools in Power BI, Tableau, or a comparable business intelligence platform.
Experience working with forecasting models and communicating results to business stakeholders in clear, practical terms, including what has changed and what it means for their planning.
SQL skills for querying, combining, and validating data, and familiarity with data preparation and transformation.
Comfort working with code and analytical scripts, including the ability to understand, troubleshoot, and improve existing workflows.
Practical experience using AI tools for analytical or technical work, with the judgment to test outputs, identify errors, and protect sensitive information.
Analytical judgment and attention to detail, including the ability to investigate discrepancies and explain what data does and does not show.
Clear communication and collaboration skills, with the ability to work with business users, manage agreed deliverables, and document work so others can use and maintain it.

Nice To Haves

2–5 years of analytics experience in book publishing or comparable entertainment or content businesses where demand varies by title, release cycle, catalog age, seasonality, and promotion.
Deeper Power BI experience, including DAX, data modeling, and report performance.
Experience with Python or another analytical scripting language, Git, Microsoft Fabric, or programmatic Power BI development using PBIP and PBIR.
Familiarity with retailer sales and inventory data or digital advertising measurement, particularly Amazon or Target.

Responsibilities

Build, improve, and maintain Power BI reports, HTML dashboards, and data models that turn business requirements into clear, usable information.
Develop reliable measures and reusable reporting components, collaborating with data colleagues on modeling, performance, and development standards.
Help develop programmatic, version-controlled reporting approaches, with opportunities to learn and apply Power BI Project and PBIR workflows.
Build, improve, and maintain forecasting models and workflows.
Monitor forecast outputs and accuracy, investigate unexpected results, and explain meaningful changes, assumptions, and limitations.
Work with business teams that use forecasts to understand their needs, gather feedback, and refine outputs for planning and decision-making.
Develop and maintain reporting on retailer sales, inventory, and ordering, including Amazon dashboards, and help users interpret performance and identify opportunities.
Analyze advertising performance across platforms such as Amazon and Target, connecting campaign results with relevant sales and business measures.
Translate findings into clear recommendations and explanations that support commercial and campaign decisions.
Use AI tools to support coding, analysis, documentation, and troubleshooting; validate generated work and handle data responsibly.
Test and reconcile outputs, document methods and run instructions, and maintain the quality and reliability of assigned reports and recurring workflows.
Troubleshoot issues with business users and technical partners, escalate source or platform problems appropriately, and support adoption through practical guidance.