Senior Manager, Marketing Data Science & Modeling

Job Description:

ABOUT US

Dow Jones is a global provider of news and business information, delivering content to consumers and organizations around the world across multiple formats, including print, digital, mobile and live events. Dow Jones has produced unrivaled quality content for more than 130 years and today has one of the world's largest news-gathering operations globally. It is home to leading publications and products including the flagship Wall Street Journal, America's largest newspaper by paid circulation; Barron's, MarketWatch, Investor's Business Daily, Factiva, Dow Jones Risk & Compliance, Dow Jones Newswires, OPIS and Chemical Market Analytics. Dow Jones is a division of News Corp (Nasdaq: NWS, NWSA; ASX: NWS, NWSLV).

ABOUT THE ROLE

Reporting to the VP of Marketing Data Science & Modeling, we are seeking a Senior Manager, Marketing Data Science & Modeling who will lead key initiatives to elevate Dow Jones’ marketing data science capabilities in support of our direct-to-consumer products.

You’ll leverage advanced analytics, predictive modeling, and machine learning to optimize marketing performance, improve customer retention, and enhance ROI. A major focus will be developing and scaling our next-gen marketing technology stack—encompassing media mix modeling, attribution, data harmonization, optimization, and scenario planning.

This is a high-impact role that bridges data science and business strategy, requiring technical depth and strong stakeholder engagement skills.

You will work in our midtown Manhattan office three days each week.

YOUR RESPONSIBILITIES

• Predictive Modeling & Machine Learning: Design, build, and deploy predictive models and machine learning solutions that power key marketing initiatives—including churn prediction, customer lifetime value, pricing optimization, and next-best-action recommendations. Continuously improve model accuracy, scalability, and real-world impact through ongoing testing and iteration.

• Media Mix Modeling & Optimization: Develop and maintain models that assess marketing spend effectiveness across channels and customer segments. Lead the data integration, harmonization, and attribution efforts required to support robust modeling. Build tools for scenario analysis, budget allocation, and performance optimization.

• Data-Driven Strategy Development: Analyze large-scale customer datasets—including demographic, behavioral, transactional, and digital engagement signals—to uncover actionable insights. Translate findings into strategic recommendations for campaign targeting, messaging, and channel optimization.

• Customer Segmentation & Lifecycle Analytics: Create advanced segmentation models to inform targeting, retention, and cross-sell/upsell strategies. Partner with marketing teams to activate segments across lifecycle touch points and evaluate performance over time.

• Model Deployment & Enablement: Operationalize models by embedding them into marketing workflows and tools. Collaborate with marketing operations and engineering to ensure model adoption, integration into platforms, and performance monitoring post-deployment.

• Team Leadership & Strategic Influence: Mentor junior team members and foster a culture of experimentation, rigor, and business alignment. Shape the marketing analytics roadmap and advocate for data-informed decision-making across functions.

• Cross-Functional Collaboration: Act as a trusted advisor to partners in marketing, product, finance, and executive leadership. Align on objectives, share insights in a clear and compelling way, and influence high-level strategic planning through analytics.

YOU HAVE

• The willingness to work in our midtown Manhattan office 3 days each week

• 10+ years of experience in data science, marketing analytics, business strategy, or related disciplines

• 5+ years managing complex technical projects in fast-paced environments with multiple stakeholders

• 1+ years of people management experience, with a strong track record of mentoring and developing talent

• A degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or similar

• Deep expertise in predictive modeling, machine learning, forecasting, and advanced analytics techniques

• Hands-on experience bu