Lead Data Scientist, Newsroom Analytics

Dow Jones & Company • New York City, NY

2d • Onsite

About The Position

The Wall Street Journal is seeking a Lead Data Scientist, Newsroom Analytics to drive our newsroom's audience-data strategy. This role is 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. It is a highly autonomous and strategic role that demands both rigorous data science and sharp analytical instincts. The Lead Data Scientist will work closely with editorial and audience leaders to surface 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, translating complex methodologies into clear recommendations, and connecting work to outcomes such as reader discovery, engagement, and return to WSJ journalism. Beyond individual output, the role serves as a technical anchor for the team, mentoring colleagues, establishing shared standards for analytical rigor, and proactively driving continuous improvements across workflows. The ideal candidate balances statistical rigor, strategic newsroom thinking, and investment in people and practices.

Requirements

• 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.
• Demonstrated ability to influence decisions without direct authority.
• Experience building models that influence content strategy, audience development, or consumer retention.

Nice To Haves

• 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.

Responsibilities

• Partner with digital strategy, coverage and product teams to identify high-impact analytical opportunities, define the right questions, and shape the data science roadmap.
• Design and build predictive and explanatory models end-to-end, from feature engineering and validation through production.
• Translate quantitative findings into clear, actionable recommendations for senior newsroom and business stakeholders, and partner with cross-functional teams for adoption.
• Own the core metrics and measurement systems that newsroom teams rely on to evaluate performance and make editorial decisions.
• Apply rigorous statistical thinking to measure real-world editorial and audience impact, using causal inference, observational methods, and controlled experimentation.
• Mentor and develop junior data team members, establishing shared standards for rigorous, production-ready analysis and building the team's collective technical capability.

Benefits

• Comprehensive and competitive benefits package covering health, retirement, wellbeing, and more.
• Optional benefits to meet diverse needs.
• Competitive and flexible compensation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed