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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Analyst - Advanced Analytics - **Company:** Chicago Public Media - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $90,000.0 - $128,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Big Data, BigQuery, Cloud Database, Data Visualization, Database Queries, Google Analytics, Statistical Hypothesis Testing, Python (Programming Language) - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ef6d6d49b5552c01 ## About the Role Do you have experience in Statistical significance testing?, * Strong SQL skills and experience working with messy and large datasets * Experience with survival analysis, causal inference, propensity modeling, regression, classification, clustering, or time series forecasting a plus. * Experience with BigQuery or similar cloud data warehouses. * Experience with A/B testing and experimental design. * Experience with data visualization tools and dashboarding. * Proficiency in Python or R for data analysis and modeling a plus * Experience building and applying predictive models in real-world settings a plus * Strong foundation in statistics, including experimentation (A/B testing) and interpreting results * Experience working with user-level behavioral data (pageviews, sessions, event data) * Ability to communicate results clearly and influence decisions * Interest in exploring how AI can support analysis and improve internal workflows * Ability to partner effectively with journalists, editors, and other editorial stakeholders, including translating data into useful insights without reducing editorial work to simple traffic optimization. * Ability to define metrics, document assumptions, and communicate data limitations clearly to stakeholders. Preferred * Experience in media, publishing, nonprofit, or subscription-based organizations * Experience defining schemas and building governed, model-ready datasets that support reproducible analysis, and enable reliable reporting * Familiarity with Google Analytics Reporting and Collaboration This role reports to the Audience Analytics Manager and works collaboratively across Chicago Public Media, including editorial leadership, product, membership, marketing, and circulation teams. ## Description We are looking for a Senior Data Analyst, Advanced Analytics to help take our analytical work to the next level through statistical modeling, forecasting, experimentation, and predictive analytics. In this role, you will lead advanced analytical projects that help the organization better understand what drives audience loyalty, newsroom engagement, membership conversion, retention, and revenue. You will improve existing propensity modeling work, develop audience scoring and segmentation approaches, build forecasting and cohort-based analyses, and identify the behavioral signals that matter most across the audience and membership funnel. This role is not purely about technical skills. The right candidate will understand the role of journalism in civic life and be able to work thoughtfully with editorial teams. They should be comfortable partnering with journalists and editors to frame good questions, interpret findings responsibly, and apply data in ways that support human judgment. General Responsibilities * Lead advanced data analysis and modeling projects that connect audience behavior, editorial engagement, product experiences, and membership outcomes. * Partner closely with teams across the organization to define high-value questions, identify meaningful metrics, and translate findings into action items. * Help editorial teams understand audience behavior in ways that are useful, responsible, and grounded in journalistic goals, distinguishing between surface-level traffic and deeper signals of loyalty, habit, trust, and audience value. * Build and improve predictive models, audience scores, segmentations, forecasts, and cohort analyses that help teams better understand behavior across the audience funnel and long-term audience value. * Support a stronger experimentation and measurement culture by advising on test design, evaluating results, and applying statistical methods such as causal inference where appropriate. * Develop reusable datasets and workflows that make advanced insights easier to apply across teams. * Translate model outputs and statistical findings into clear recommendations and tools. * Identify opportunities where more sophisticated analysis, modeling, or data science methods can improve decision making and organizational outcomes. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Making Data Warehouses fast. 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