Job description

Job Description: The Wall Street Journal is seeking a Lead Data Scientist, Newsroom Analytics to drive our newsroom s audience-data strategy. Reporting to the Senior Manager, Newsroom Data, you will be embedded in one of the world s most influential newsrooms, working directly with newsroom coverage, audience, and product strategy teams on the decisions that shape how news is reported, prioritized, and delivered to millions of readers. This is a highly autonomous and strategic role that demands both rigorous data science and sharp analytical instincts in equal measure. Working closely with editorial and audience leaders, you ll surface the right problems and own the full arc from solution design to adoption, building the metrics, models, and forecasts that teams rely on. This includes developing tools teams actually use, translating complex methodologies into clear recommendations, and consistently connecting your work to outcomes that matter: how readers discover, engage with, and return to WSJ journalism. Beyond your own output, you will serve as a technical anchor for the team, mentoring colleagues, establishing shared standards for analytical rigor, and proactively driving continuous improvements across our workflows. The ideal candidate seamlessly balances statistical rigor, strategic newsroom thinking, and a genuine investment in the people and practices around them. This position will be based in our New York office. You will: Partner with our digital strategy, coverage and product teams to identify the highest-impact analytical opportunities, define the right questions, and shape the data science roadmap around problems that drive real newsroom outcomes. Design and build predictive and explanatory models end-to-end, from feature engineering and validation through production, making principled tradeoffs between complexity and interpretability along the way. Translate quantitative findings into clear, actionable recommendations for senior newsroom and business stakeholders, and partner with cross-functional teams to see those recommendations through to adoption. Own the core metrics and measurement systems that newsroom teams rely on to evaluate performance and make editorial decisions, ensuring they are accurate, well-documented, and trusted. Apply rigorous statistical thinking to measure real-world editorial and audience impact, drawing on causal inference and observational methods alongside controlled experimentation to isolate what s actually driving outcomes. Mentor and develop junior data team members, establishing shared standards for rigorous, production-ready analysis and building the team s collective technical capability over time. You have: 5 years of experience in data science, analytics, or applied machine learning, preferably in a media, publishing, or subscription-based environment. Proven ability to own models end-to-end in a lean team setting, including scheduling, maintaining, and iterating on outputs using orchestration tools such as Airflow. Strong proficiency in Python including feature engineering, model training, validation, and interpretation, with experience maintaining production-quality, reproducible code in Git. Advanced SQL and hands-on experience with large-scale data warehouses (Snowflake/BigQuery) as well as ETL workflows/analytics engineering frameworks (dbt). Experience applying causal inference and statistical methods to measure real-world outcomes from observational data. Strong communication skills with the ability to frame quantitative findings as clear business or editorial recommendations for senior non-technical stakeholders, and a demonstrated ability to influence decisions without direct authority. Experience building models that influence content strategy, audience development, or consumer retention. Standout candidates will have strengths in one or more areas of the following: Experience with NLP or text analysis methods, including topic modeling, classification, or entity extraction applied to content data. Familiarity with off-platform attribution and audience measurement, specifically modeling the relationship between distributed content, platform referrals, and downstream subscription or engagement outcomes. Experience leveraging AI to democratize data and enable faster time-to-insight. To apply, please submit a resume and a cover letter explaining how your skills, experience and interests align with the expectations of the role by July 28th. Applications will be reviewed on a rolling basis, and we encourage early submission as the position may be filled before the deadline. The Journal’s reporters, editors, developers, and audio and visual journalists create important and impactful stories, firmly rooted in fact and adhering to the highest ethical standards. We report without fear or bias, and we maintain a proper sense of perspective, detachment and objectivity in our reporting. *LI-JA1-WSJ. Reasonable accommodation: Dow Jones, Making Careers Newsworthy - All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status. EEO/AA/M/F/Disabled/Vets. Dow Jones is committed to providing reasonable accommodation for qualified individuals with disabilities, in our job application and/or interview process. If you need assistance or accommodation in completing your application, due to a disability, email us at talentresourceteam dowjones.com. Please put Reasonable Accommodation in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic under applicable law. EEO/Disabled/Vets Reasonable Accommodation We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at talentresourceteam@dowjones.com. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates. Please refer to the privacy notice at the bottom of this page for submitting any data access, deletion, or other data subject rights requests, where permitted under your local laws and regulations. Business Area: Dow Jones - News - WSJ Job Category: Data Analytics/Warehousing & Business Intelligence Union Status: Union role Base Pay Range: - We’re committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate’s experience, skills, location, and other relevant factors. For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions. For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees.

Requirements

Must-haves

Design and build predictive and explanatory models end-to-end, from feature engineering and validation through production, making principled tradeoffs between complexity and interpretability along the way.
Translate quantitative findings into clear, actionable recommendations for senior newsroom and business stakeholders, and partner with cross-functional teams to see those recommendations through to adoption.
Own the core metrics and measurement systems that newsroom teams rely on to evaluate performance and make editorial decisions, ensuring they are accurate, well-documented, and trusted.
Mentor and develop junior data team members, establishing shared standards for rigorous, production-ready analysis and building the team s collective technical capability over time.
5 years of experience in data science, analytics, or applied machine learning, preferably in a media, publishing, or subscription-based environment.
Proven ability to own models end-to-end in a lean team setting, including scheduling, maintaining, and iterating on outputs using orchestration tools such as Airflow.
Strong proficiency in Python including feature engineering, model training, validation, and interpretation, with experience maintaining production-quality, reproducible code in Git.
Advanced SQL and hands-on experience with large-scale data warehouses (Snowflake/BigQuery) as well as ETL workflows/analytics engineering frameworks (dbt).
Experience applying causal inference and statistical methods to measure real-world outcomes from observational data.
Experience building models that influence content strategy, audience development, or consumer retention.
Standout candidates will have strengths in one or more areas of the following:
Experience with NLP or text analysis methods, including topic modeling, classification, or entity extraction applied to content data.
Familiarity with off-platform attribution and audience measurement, specifically modeling the relationship between distributed content, platform referrals, and downstream subscription or engagement outcomes.
Experience leveraging AI to democratize data and enable faster time-to-insight.
Dow Jones - News - WSJ
Data Analytics/Warehousing & Business Intelligence
For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees.

Nice-to-haves

For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonsqlai

Platform: workday
Effort: long