Senior Analytics Engineer – Media Forecasting & Data Systems

BIA Advisory Services is seeking a Senior Analytics Engineer - Media Forecasting & Data Systems to help build, maintain, and advance the data infrastructure behind BIA's industry-leading local advertising forecasts and market intelligence products.

Working across television, radio, streaming, digital, and emerging media channels, this role will support the systems and analytical workflows used to collect, organize, transform, validate, analyze, and publish BIA's forecasting data across broadcast television, radio, streaming, digital, and emerging media channels.

The position combines elements of analytics engineering, data engineering, database development, forecasting support, and broadcast and digital media analytics. The successful candidate will work closely with the Vice President of Forecasting & Data Analysis to translate research methodologies, business assumptions, and media industry knowledge into reliable, scalable, repeatable, and well-documented technical processes.

This is not solely a traditional IT or software engineering role. The ideal candidate will understand the analytical purpose behind the data, recognize when outputs do not appear reasonable, investigate inconsistencies, and collaborate effectively with researchers, analysts, and business stakeholders.

Experience working with digital and traditional media, local advertising, audience measurement, media research, advertising data, or related industry analytics is highly desirable. Tips:
Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall.

• Maintain and improve database tables, views, schemas, queries, and data structures supporting BIA’s forecasting and analytical processes.
• Design database structures that improve accessibility, consistency, scalability, and reliability of forecast inputs and outputs.
• Help migrate spreadsheet-based and manually managed processes into standardized database workflows.
• Monitor database dependencies and help resolve data-loading, performance, access, and data-quality issues.
• Maintain clear relationships between source data, intermediate tables, forecast models, analytical outputs, and published deliverables.
• Support the organization and management of media, advertising, audience, market, and geographic datasets.

• Build and maintain repeatable processes for ingesting data from internal and external sources.
• Develop, maintain, and troubleshoot R, Python, and SQL scripts used for data preparation, forecasting, validation, reporting, and automation.
• Automate recurring data-loading, transformation, reconciliation, quality-control, and output-generation tasks.
• Reduce reliance on manual processes, hard-coded file paths, and one-time workflows.
• Improve the ability to rerun workflows safely when source data, assumptions, or forecasting methodologies change.
• Establish appropriate logging, error handling, process controls, and workflow monitoring.
• Support integration of data received from media research providers, vendors, partners, APIs, spreadsheets, regulatory sources, and other external datasets.

• Work with the Vice President of Forecasting & Data Analysis to translate forecasting methodologies and research assumptions into transparent and maintainable code.
• Support forecasting and analytical processes across television, radio, streaming, digital, and emerging local media channels, incorporating audience measurement, advertising revenue, and market intelligence datasets into forecasting workflows.
• Prepare forecast inputs and outputs for methodological review, business analysis, and publication.
• Help investigate unexpected results, data discrepancies, outliers, and changes in historical trends.
• Apply knowledge of media industry data, audience measurement, advertising trends, and market dynamics to improve forecast quality and identify anomalies.
• Ensure market-level, media-level, category-level, and national forecast outputs reconcile appropriately.
• Support statistical, time-series, econometric, or Bayesian modeling workflows as needed.
• Maintain a clear separation between source data, assumptions, modeled results, and final forecast adjustments.

• Develop automated and manual quality control procedures for major data and forecasting workflows.
• Validate that source totals, database values, market allocations, historical…