data scientist

We’re looking for a Data Scientist to join a team focused on advertising inventory modeling and capacity forecasting for subscriber base. This team builds models that match commercials and ads to subscriber profiles based on viewing behavior, identifies gaps in that targeting, and works to fill them through marketing data. A core part of the role is forecasting available advertising capacity - balancing sold vs. unsold airtime, and understanding the difference between acquired inventory and own inventory, as well as true demand vs. true capacity. The team works with a blend of proprietary subscriber data and third-party data sources. Notably, data- previously treated as third-party - became first-party data as of a recent company merger, and this shift is actively being incorporated into forecasting models. This is a great opportunity for a data scientist who enjoys applied modeling work with real business impact, in a fully cloud-based environment.

What You’ll Do

• Build and maintain models that align advertising inventory with subscriber viewing profiles
• Forecast advertising capacity, including sold vs. unsold airtime and acquired vs. owned inventory
• Work with both first-party and third-party data sources
• Incorporate newly integrated first-party data into existing forecasting models
• Collaborate with a cross-functional team, following established CI/CD practices
• Take on light data engineering tasks as needed to support modeling work

• Solid, practical data science experience - this is not a role requiring deep specialization or “absolute expert” level skills
• Someone who understands what they’re doing and can work independently on modeling problems
• Experience working as part of a team, ideally with exposure to CI/CD processes
• Comfort doing some data engineering work in support of modeling (not a pure modeling-only candidate)
• Candidates from a Finance background are not a strong fit for this role

Tech Stack

• Languages/Tools: Python, SQL
• Data Warehouse: Snowflake (corporate data warehouse)
• Cloud: AWS (fully cloud-based - no on-prem infrastructure)
• ML Tooling: Various data science libraries
• Nice to Have: SageMaker, Airflow, PySpark

ManpowerGroup® (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills. Our expert family of brands - Manpower, Experis, Talent Solutions, and Jefferson Wells - creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2022 ManpowerGroup was named one of the World’s Most Ethical Companies for the 13th year - all confirming our position as the brand of choice for