Senior Applied Data Scientist

Be Part of What’s Next

Senior Applied Data Scientist, BI Engineering

Help shape the next evolution of Hearst Magazines’ analytics maturity—moving from descriptive reporting to predictive and prescriptive insights that power smarter decisions. In this role, you’ll bridge BI Engineering and Data Science to build scalable models, simulations, and optimization frameworks that drive revenue growth, audience engagement, and executive decision-making.

About Hearst Magazines (Why Us?)

Hearst Magazines’ portfolio of more than 30 iconic brands in the U.S.—including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper’s BAZAAR, and Popular Mechanics — inspires, entertains, and builds new and bold experiences for an engaged and growing audience across digital, video, social and print, reaching nearly 130 million readers and site visitors each month. With sophisticated content creation, cutting-edge technology, and industry-leading data capabilities, we make media and products that move people across all platforms. We are a global media company that publishes nearly 200 magazine editions and 175 websites around the world—and together, we are shaping what’s next.

Key Responsibilities (What You’re Doing)

• Develop and maintain analytical and semantic layers and data models that integrate, clean, and transform data from multiple sources into unified, analytics-ready datasets that enable fast querying for reporting and analysis.
• Contribute to the organization’s data maturity roadmap by evolving the BI foundation from descriptive toward predictive and prescriptive analytics.
• Partner with BI Engineering to leverage governed analytical and semantic layers in BigQuery. 
• Collaborate with BI Engineers to operationalize model outputs as analytical tables or scheduled DBT/Airflow jobs.
• Develop and validate predictive and prescriptive models that translate business questions into actionable insights for strategic and operational decision-making.
• Build “what-if” simulations and optimization frameworks to evaluate business scenarios and guide planning.
• Conduct statistical analysis to assess the quality, consistency, and health of datasets, ensuring reliable inputs for modeling and decision support.
• Design and analyze controlled experiments to measure the impact of product, audience, or marketing initiatives.
• Present results and recommendations through clear visualizations, concise narratives, and executive-facing summaries.

Qualifications (What We’re Looking For)

• 3–6 years of experience in applied data science, predictive analytics, or quantitative modeling.
• Proficiency in Python (Pandas, Scikit-Learn, Statsmodels, Prophet) and SQL (BigQuery preferred).
• Hands-on experience with statistical, forecasting, and optimization techniques applied to real-world business challenges.
• Ability to perform data quality assessments and statistical diagnostics to monitor the health and stability of analytical datasets.
• Strong understanding of experimentation design, causal inference, and model evaluation methods.
• Familiarity with data orchestration and modeling tools such as DBT, Airflow, or similar.
• Comfortable working within a cloud data warehouse environment and collaborating closely with BI and Engineering teams.
• Excellent communication and data storytelling skills — able to translate complex models into clear business insights.
  Nice to have: experience in digital media, marketing analytics, or revenue optimization; familiarity with Looker or other semantic-layer tools.
• In-office requirement: New York-based, hybrid role with 4 days per week in the office.

Preferred Skills:

• Exposure to marketing, media, or commerce analytics, including traffic, audience, or revenue optimization use cases.
• Understanding of Bayesian statistics, time-series forecasting, or optimization methods for scenario simulation.
• Experience building forecast validation and monitoring frameworks to track model drift and accuracy over time.
• Working knowledge of data visualization and narrative storytelling best practices (e.g., Looker, Tableau, or custom Python visualizations).
• Familiarity with GCP tools (BigQuery, Cloud Composer, Vertex AI Workbench, etc.) or equivalent AWS/Azure environments.
• Interest in generative AI and LLM applications that enhance business intelligence (e.g., automated insights, natural-language querying).

Benefits (What We Offer)

At Hearst Magazines, we invest in your success and well-being—professionally and personally. Benefits include:

• Work with the Best: Collaborate with top-tier professionals across media, advertising, tech, fashion, lifestyle, and publishing, shaping the future of these dynamic industries.
• Grow Your Skills: Unlock your potential with access to innovative training programs, immersive workshops, and exclusive industry events.
• Work-Life Harmony: Enjoy the flexibility of hybrid work, empowering you to balance professional success with personal priorities.
• Foster Connection & Belonging: Join our Employee Resource Groups and help create a welcoming workplace where everyone feels valued and empowered.
• Wellness First: Prioritize your well-being with a comprehensive benefits package that includes medical, dental, and vision insurance from Day 1.
• Plan for Your Financial Future: Enjoy competitive financial perks, including a 401(k) plan with a generous company match.

The base salary for this role is between $133,000 - $178,000. The actual base pay offered is dependent upon many factors, such as: transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future.

Hearst is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.