Data Scientist, Demand Modeling

Key Skills

Microsoft-Excel, Java Programming, Python Programming, SQL, Data science techniques, Google BigQuery, Google Cloud Platform (GCP)

Job Description

As a demand modeling data scientist in the Data Science team, you’ll be responsible for developing and maintaining forecasting models for growth and revenue. You will be creating KPI and metricbased reporting and presenting actionable data analyses and scenarios. This position will work closely with Growth, Sales & Retention business teams, as well as the Revenue Operations, Data Engineering, and other business teams across Gannett to compile, consolidate, model, and analyze data to support planning and decisionmaking.

Our ideal candidate is a collaborative and innovative problem solver, who is profoundly handson and is passionate about applying stateoftheart and innovative solution frameworks to solve business problems and identify process improvement opportunities.

How you’ll make an impact:

• Use statistical modeling and analytics to understand how business decisions impact our bottomline.
• Build forecasts and projections for key business metrics to assess current performance and set performance goals for crossfunctional business teams.
• Partner with Growth and Retention teams to create customized reporting and business models showcasing the impacts of our tactics and strategies for acquisition, retention, and revenue.
• Provide financial analysis and predictive modeling for existing product changes and new product roll outs, leveraging historical sales and traffic data to make financial projections.
• Provide pricing analysis on sale offers to optimize both subscriber volume and overall revenue.
• Benchmark performance across marketing channels for digital subscriptions including CAC analyses.
• Understand the data and Gannett business model deeply and effectively translate model outcomes and insights into actions and recommendations that lead to decisions and measurable ROI.

What you’ll bring:

• A Bachelor or MS degree in a quantitative field like data science, finance, accounting, economics etc.
• 35 years of experience in building budget and revenue forecast models.
• Experience in managing initiatives or teams. Experience in articulating data stories and insights to Clevel executives.
• Handson experience in advanced data analysis skills and tools – MS Excel superpowers (pivot tables, lookups, macros etc.), Python and SQL.
• Proficiency in statistical modeling like regression, and timeseries forecasting is a plus.
• Experience in cloud data platforms like GCP, BigQuery, Data Studio is a plus.
• Experience working with Google web analytics data is a plus but not required.
• Excellent communication and storytelling ability with track record of translating model results into business insights, and then into actionable recommendations.