Senior Data Analyst - Advanced Analytics

Chicago Public Media•Chicago, IL

19h•Hybrid

About The Position

Chicago Public Media is seeking a Senior Data Analyst, Advanced Analytics to elevate its analytical capabilities through statistical modeling, forecasting, experimentation, and predictive analytics. This role will spearhead advanced analytical projects aimed at enhancing the organization's understanding of audience loyalty drivers, newsroom engagement, membership conversion and retention, and revenue generation. The analyst will refine existing propensity modeling, develop audience scoring and segmentation strategies, construct forecasting and cohort-based analyses, and pinpoint critical behavioral signals across the audience and membership funnel. Beyond technical proficiency, the ideal candidate will possess an understanding of journalism's role in civic life and collaborate effectively with editorial teams. They should be adept at partnering with journalists and editors to formulate pertinent questions, interpret findings responsibly, and apply data to support human judgment.

Requirements

Strong SQL skills and experience working with messy and large datasets
Experience with BigQuery or similar cloud data warehouses.
Experience with A/B testing and experimental design.
Experience with data visualization tools and dashboarding.
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.

Nice To Haves

Experience with survival analysis, causal inference, propensity modeling, regression, classification, clustering, or time series forecasting a plus.
Proficiency in Python or R for data analysis and modeling a plus
Experience building and applying predictive models in real-world settings a plus
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

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.