Senior Data Scientist, Data & AI Team

Be Part of What's Next 

Hearst Magazines is seeking a visionary and hands-on Senior Data Scientist to join our dynamic Data & AI team. In this pivotal role, you will be a key player in architecting and implementing the advanced data models that power personalized user experiences, drive our next-generation advertising products, and provide deep, actionable insights to our world-class editorial and commercial teams. You will tackle complex challenges at the intersection of machine learning, user behavior, and content strategy, with a direct impact on the trajectory of our iconic brands.

• →Lead and Innovate: Design, develop, and deploy sophisticated machine learning models to address core business challenges, including user segmentation, content recommendation, churn prediction, and lifetime value modeling.
• →Strategic Impact: Partner with product, engineering, editorial, and revenue teams to identify and execute on data science initiatives that drive measurable business outcomes.
• →Full-Cycle Development: Own the end-to-end data science workflow, from hypothesis generation and data exploration to model building, validation, and deployment into production environments.
• →Advanced Analytics: Conduct in-depth exploratory analysis of large, complex datasets to uncover hidden patterns, trends, and opportunities for innovation.
• →Mentorship: Provide guidance and mentorship to junior data scientists and analysts, fostering a culture of technical excellence and collaborative problem-solving.
• →Thought Leadership: Stay at the forefront of advancements in data science and machine learning, and champion the adoption of new technologies and methodologies within the organization.

• Experience: 7+ years of experience in a data science role, with a proven track record ofdeveloping and deploying impactful machine learning models in a production environment.
• Technical Expertise: 
  • Expert proficiency in Python and SQL.
  • Deep understanding of machine learning algorithms (e.g., regression, classification, clustering, NLP) and statistical modeling.
  • Hands-on experience with machine learning libraries and frameworks such as Scikit-learn, TensorFlow, or PyTorch.
  • Experience with big data technologies (e.g., Spark, BigQuery) and cloud platforms (GCP, AWS).
• Strategic Mindset: Ability to translate complex business problems into well-defined data science projects and communicate technical concepts effectively to non-technical stakeholders. 
• Leadership: Demonstrated ability to lead projects, mentor junior team members, and collaborate effectively across cross-functional teams.
• Education: Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline is preferred.
• This is a hybrid position based in New York City, with an in-office requirement of four days per week.