Data Scientist

Job Description – add details here

Summary
We’re looking for a Senior Data Scientist with a strong foundation in predictive modeling, clustering, and statistical analysis. This role combines hands-on machine learning with close collaboration across business and product teams to build production-ready models that forecast content performance and reveal content insights. The ideal candidate is fluent in modern MLOps tools, proactively explores new approaches, and iterates based on user feedback to ensure solutions are interpretable, trusted, and adopted across the organization.
Experience in the media/entertainment industry is a strong advantage, or other creative industries. The ideal candidate has experience building DS solutions to support, not replace, human judgment, and therefore has experience optimizing for results beyond just accuracy improvements, such as enriching insights and discussions.

Responsibilities
Build and iterate on predictive models to project content performanceTest different model types (e.g., gradient boosting, regression) and iterate based on accuracy and user interpretability needsComplete model experiments to validate hypothesesProactively identify opportunities to improve performance and contribute to model development roadmap
Explore and segment content typesUse clustering, principal component analysis, and other unsupervised methods to identify patterns in performance drivers and content typesExperiment with GenAI to enrich data (e.g., augmenting metadata tagging or generating synthetic attributes)
Collaborate with business users to refine models and drive adoptionInfuse models and model approach with users’ domain expertise and decision-making workflowsPresent early model outputs in accessible ways to solicit feedback and identify gaps, overlooked variables, and implicit assumptions from usersInterpret user feedback and adapt model design and underlying data to prioritize interpretability, usability, or explainability where required to build trust and drive adoption
Maintain and monitor modelsWork with ML Engineers to deploy models in production, including API endpoints, and establish ML pipelineContribute to shared libraries and modeling best practices across the data science team
Partner with product and platform teams to deliver impactContribute to design and implementation of new products where data science models will be embedded, built by agile product PODsCollaborate with data architects, data engineers, and broader platform team to facilitate technical discussions and enrich the data available for data science
Requirements4+ years of experience Proven experience as a Data Scientist4+ years of experience Python and common ML library experience (e.g., scikit-learn, XGBoost, pandas).4+ years of experience Familiarity with AWS tools, especially SageMaker, or equivalent cloud-based ML environments
Nice to Have Skills / Preferred RequirementsExperience in media & entertainment industry is a strong advantage but not requiredSQL fluency is a plus
Soft Skills:Curiosity and capability to work in an experimental stage of development to test hypotheses and adjust approaches to deliver the most value to business usersExperience building predictive models, especially with limited sample sizesUnderstanding of clustering and dimensionality reduction techniquesExposure to generative AI models (e.g., LLMs, diffusion models) and an interest in applying them to real-world data problemsStrong communication skills and the ability to translate data science work into business value as well as translate business user needs into data science
Technology Requirements:Strong skills in Python and common ML libraries (e.g., scikit-learn, XGBoost, pandas).Familiarity with AWS tools, especially SageMaker, or equivalent cloud-based ML environmentsExperience building predictive models, especially with limited sample sizesUnderstanding of clustering and dimensionality reduction techniquesExposure to generative AI models (e.g., LLMs, diffusion models) and an interest in applying them to real-world data problems

Skills and Requirements – add details here

Requirements4+ years of experience Proven experience as a Data Scientist4+ years of experience Python and common ML library experience (e.g., scikit-learn, XGBoost, pandas).4+ years of experience Familiarity with AWS tools, especially SageMaker, or equivalent cloud-based ML environments
Nice to Have Skills / Preferred RequirementsExperience in media & entertainment industry is a strong advantage but not requiredSQL fluency is a plus
Soft Skills:Curiosity and capability to work in an experimental stage of development to test hypotheses and adjust approaches to deliver the most value to business usersExperience building predictive models, especially with limited sample sizesUnderstanding of clustering and dimensionality reduction techniquesExposure to generative AI models (e.g., LLMs, diffusion models) and an interest in applying them to real-world data problemsStrong communication skills and the ability to translate data science work into business value as well as translate business user needs into data science