Data Journalist, AI & Automation

ConsumerAffairs

About The Position

As a Data Journalist specializing in AI and automation, you’ll work at the intersection of data, technology, research, and storytelling to help produce original, data-driven content for ConsumerAffairs. You’ll turn complex datasets into clear, compelling stories that are useful to consumers, earn media attention, and strengthen ConsumerAffairs’ authority. This role is highly analytical and increasingly technical. In addition to developing story ideas and interpreting data, you’ll help us build smarter ways to research, analyze, QA, and produce data-driven content. That includes experimenting with AI tools and building and improving workflows to make repetitive work faster and more scalable. You don’t need to be a software engineer, but you should be comfortable working with data beyond a basic spreadsheet. We’re looking for someone who understands quantitative analysis, can learn technical tools quickly, and is interested in using AI, automation, and code to solve editorial problems. You might come from journalism, data journalism, statistics, economics, research, computer science, communications, or another related field. What matters most is your ability to work confidently with data, analyze it critically, identify the story behind the numbers, and continuously look for better ways to do the work.

Requirements

Bachelor’s degree in journalism, communications, data analytics, statistics, computer science, or a related field, or equivalent relevant experience.
1-3 years of experience in journalism, content, research, data storytelling, data visualization, digital PR, or a related area. Internships, academic projects, freelance work, and relevant coursework are welcome.
Strong quantitative and statistical reasoning, including the ability to work confidently with percentages, rates, averages, distributions, rankings, changes over time, and other common forms of analysis.
Strong writing and communication skills, with the ability to explain data and complex ideas clearly and accurately.
Interest in researching and evaluating credible data sources, including government and other publicly available datasets; prior experience is a plus.
Detail-oriented and committed to accuracy, with the ability to question results that seem unusual or inconsistent.
Strong organizational skills and the ability to manage multiple projects, priorities, and deadlines.
Strong proficiency in Excel or Google Sheets, including formulas, filtering, sorting, lookups, conditional logic, pivot tables, and working with larger datasets.
Working knowledge of basic statistical analysis and an understanding of how to choose appropriate ways to analyze and compare data.
Ability to inspect, clean, transform, and validate datasets from multiple sources.
Comfortable using APIs.
Strong interest in building AI-assisted and automated workflows.
Ability to use AI tools thoughtfully for research, coding, analysis, ideation, and production while independently validating outputs and maintaining editorial standards.

Nice To Haves

Experience with tools such as ChatGPT, Claude, Gemini, Zapier, n8n, or similar platforms is a plus.
Interest in data visualization; experience with Datawrapper, Flourish, Tableau, Infogram, or similar platforms is a plus.
Familiarity with AP Style and digital publishing is a plus.

Responsibilities

Help develop original, data-driven story ideas that are timely, relevant, and useful to consumers.
Research credible data sources and evaluate whether potential story ideas can be supported by reliable data.
Help develop clear, defensible methodologies for analyzing data and measuring the topics we cover.
Interpret datasets to identify meaningful trends, comparisons, outliers, and other findings that can shape the story.
Think critically about what the data does — and does not — support, including limitations that should be considered when presenting findings.
Identify opportunities to bring findings to life through charts, maps, tables, rankings, and other data visualizations.
Turn research and data findings into clear editorial direction, including story angles, outlines, key findings, and guidance for freelance writers.
Coordinate with data analysts and freelance writers throughout the production process, communicating expectations, answering questions, and keeping projects on track.
Review and QA analysts’ work for accuracy, including source data, calculations, formulas, methodologies, and final results.
Review writer drafts to ensure they follow the intended story structure and research direction and highlight the most important findings.
Manage multiple projects at different stages of production while meeting deadlines and keeping stakeholders informed.
Collaborate with editors, designers, Digital PR teammates, and other stakeholders to move projects from initial concept through publication.
Identify opportunities to use AI and automation to make research, data analysis, QA, and production workflows faster and more scalable.
Build, test, and improve AI-assisted or automated workflows for repetitive production tasks while maintaining human review and editorial standards.
Experiment with new tools and approaches that can improve the efficiency, accuracy, and consistency of data-driven projects.
Document successful workflows and help integrate them into the team’s production process.
Evaluate AI-generated outputs critically and independently validate data, calculations, sources, and findings before they are used in published work.
Stay curious about consumer trends, news, emerging datasets, and new approaches to data storytelling.
Consider how research findings can be framed and presented to resonate with both consumers and journalists.
Contribute ideas for improving our research, production processes, storytelling, and visual presentation.
Use performance results and team feedback to understand what makes data-driven content successful and apply those lessons to future projects.