Data Scientist

The Data Science group which is a part of Gannett's Enterprise Data Management 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 will do:

As a data scientist in the Audience Science hub, you will be part of a team that is leveraging machine learning and Artificial Intelligence (AI) techniques and algorithms to analyze humongous volumes of structured and unstructured customer data to unlock actionable insights and opportunities that help us drive user value and retention. Your role will directly impact how millions of our users across the communities 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 while following our cybersecurity standards. In this role, you will work collaboratively with analysts, engineers, and stakeholders to support the growth of our digital audience and drive insights that will inform our editorial, marketing, and product strategies.

How you will make an impact:

• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions that drive business value.
• Analyze large and complex datasets, including clickstream data, demographic data, and other relevant sources.
• Extract and collect data from external data sources while strictly adhering to our privacy-first and information security standards.
• Develop and implement predictive models to identify patterns, trends, and insights that contribute to a deeper understanding of audience behavior and preferences.
• Apply statistical analysis techniques, data mining, and machine learning methods to extract actionable insights and drive data-informed decision-making.
• Utilize programming languages (e.g., Python, R) and data manipulation tools (e.g., SQL) to clean, transform, and process data for analysis.
• Collaborate with internal stakeholders to define key performance indicators (KPIs) and work with the data visualization team to develop dashboards and reports to track and communicate audience insights.
• Stay up-to-date with the latest industry trends, tools, and techniques in data science and AI to apply them to enhance our data analytics capabilities.
• Communicate findings and recommendations to technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations.
• Explore new data sources, tools, and technologies to continuously improve our data infrastructure and analytics capabilities.

• Bachelor's or master's degree in a quantitative field such as Statistics, Data Science, Computer Science, Mathematics, or a related field.
• 0-1+ years of experience in a data science role, preferably in a media or digital marketing environment.
• Demonstrated experience in working with data analysis, statistical modeling, and building and evaluating machine learning models. Experience in deploying and monitoring machine learning solutions in production is a plus.
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and querying using SQL in relational databases.
• Familiarity with data visualization tools (e.g., Tableau, Looker, DataStudio) to effectively communicate insights.
• Experience working in cloud data platforms like GCP, Azure, and AWS is a plus.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and distill it into meaningful insights.
• Knowledge and proficiency in working with Google web analytics data is a plus.
• Experience on working with Natural Language Processing (NLP) and Large Language Models (LLM) to enhance data-driven insights and solutions.
• Excellent communication, storytelling, and presentation skills to effectively convey technical concepts to both technical and non-technical stakeholders. Having a track record of translating model results into business insights, and then into actionable recommendations is a plus
• A passion for working with data and uncovering hidden patterns that drive business impact.