Sr. Data Scientist, Audience Science
Our current portfolio of media assets includes USA TODAY, local media organizations in 46 states in the U.S., and Newsquest, a wholly owned subsidiary operating in the United Kingdom with more than 120 local news media brands. Gannett also owns the digital marketing services companies ReachLocal, Inc., UpCurve, Inc., and WordStream, Inc., which are marketed under the LOCALiQ brand, and runs the largest media-owned events business in the U.S., USA TODAY NETWORK Ventures.
To connect with us, visit www.gannett.com.
Sr. Data Scientist, Audience Science
The Enterprise Data Science team which is a part of Gannett’s Enterprise Data Organization designs and develops machine learning models and decision science solutions that enable our cross-functional partners across Product, Content and Marketing teams to predict performance, better understand audiences and then engage them with meaningful and delightful content experiences.
What you’ll do:
In this exciting leadership opportunity, you will have the unique opportunity to roll up your sleeves and lead our core data science hub for the most central part of our business – Audience! Your role will directly impact how millions of our users across the communities we serve in connect and engage with our content and our products.
Our ideal candidate is a collaborative and innovative problem solver, who is profoundly hands-on and is passionate about applying state-of-the-art solution frameworks and machine learning techniques to develop behavioral segments, audience propensities and other data products that embed strategic audience insights into Gannett’s daily decisions and value chains.
How you’ll make an impact:
- Develop and/or improve predictive models to identify lookalike and high-propensity audiences to be targeted for acquisition, retention, and engagement.
- Build behavior segments and personas by analyzing user preferences and affinities across the customer journey.
- Analyze behavioral trends to uncover opportunities to improve overall personalization, as well as content, and product performance.
- Understand the data deeply and effectively translate model outcomes and insights into actions and recommendations that lead to decisions and measurable ROI.
What you’ll bring:
- MS or PhD in a quantitative field, with 8+ years of hands-on experience in building, evaluating, deploying, and monitoring machine learning solutions in production to solve business problems.
- Advanced knowledge of models for classification, regression, and time-series modeling. Deep learning expertise is preferred.
- Experience working in cloud data platforms like GCP, Big Query etc.
- Experience working with Google web analytics data is a plus.
- Excellent communication and storytelling ability with track record of translating model results into business insights, and then into actionable recommendations
Other details
- Job Family Data Strategy & Analytics
- Job Function Technology
- Pay Type Salary
- United States
- Virtual