Senior Data Analyst – Advanced Analytics

Jobtailor; Chicago (IL); On-site; USD 110,000 - 160,000; Full time

Job summary

Jobtailor is seeking an experienced data analyst to lead advanced analysis and modeling projects that connect audience behavior, editorial engagement, product experiences, and membership outcomes.

You will partner with teams across the organization to define high-value questions, identify meaningful metrics, and translate findings into actionable recommendations for editors, product managers, and other stakeholders.

Qualifications

• Strong SQL skills and experience with large, messy datasets.
• Experience with survival analysis, causal inference, and predictive modeling.
• Experience with BigQuery and cloud data warehouses.
• Experience with A/B testing and experimental design.
• Experience with Python or R for analysis.
• Ability to translate data into insights for journalists.

Responsibilities

• Lead advanced data analysis and modeling projects connecting audience behavior, editorial engagement, product experiences, and membership outcomes.
• Partner with teams to define high-value questions, identify metrics, and translate findings into actions.
• Help editorial teams understand audience behavior in useful, journalistic terms distinguishing signals of loyalty.
• Build and improve predictive models, audience scores, segmentations, forecasts, and cohorts.
• Support experimentation and measurement culture by advising on test design and results interpretation.
• Develop reusable datasets and workflows for cross-team application.
• Translate model outputs into clear recommendations and tools.
• Identify opportunities where advanced analysis can improve decision making.

Skills

SQL

Survival analysis

Causal inference

Propensity modeling

Regression

Classification

Clustering

Time series

BigQuery

A/B testing

Data visualization

Python

R

Predictive modeling

Statistics

User analytics

Communication

AI in workflows

Journalist collaboration

Job description

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.

Requirements

• 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.