Job Description
Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported by media industry leaders, Comcast, NBCUniversal and Sky.
When you join our team, you’ll work across our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere, powering streaming across more than 70 countries globally.
And the evolution doesn’t stop there. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another.
We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience.
But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive.
As part of the Decision Sciences team, the Sr. Lead Data Scientist will be responsible for creating analytical solutions for one or more verticals of NBCU’s video streaming service including, but not limited to, dynamic pricing, messaging optimization, CRM solutions, and customer value assessment.
In this role, the Sr. Lead Data Scientist will use advanced data science methodologies including causal uplift modeling, contextual and non-contextual bandits, experimentation, and Gen AI (LLMs).
They will work closely with business owners, teammates and engineers to build state-of-the-art algorithmic targeting solutions for a dynamic media platform.
They will be responsible for building, maintaining, and testing robust production ready systems that may need to serve low latency predictions.
Responsibilities include, but are not limited to :
Lead existing and develop new projects related to the development of analytical models using machine learning, causal uplift modeling, and Gen AI techniques.
Provide mentorship to teammates via pairing and code reviews
Expertly communicates work and project implications to stakeholders of varying technical expertise
Conduct rigorous cross-validation and backtesting of model performance.
Proficiency with CI / CD processes and contributes to a sustainable and robust codebase
Experience with batch jobs / data pipelines and is comfortable deploying through these systems (i.e. Airflow, Luigi, Composer)
Build and interact with production systems for serving machine learning predictions.
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