Job Location – Burbank, CA (Hybrid - 3x Per Week Onsite)

Type - Contract (10 Months with Possible Extension)

Pay Rate – $78.00 - $84.00 Per Hour

W2 Candidates Only

Responsibilities

Build and iterate on predictive models to project content performance

• Test different model types (e.g., gradient boosting, regression) and iterate based on accuracy and user interpretability needs
• Complete model experiments to validate hypotheses
• Proactively identify opportunities to improve performance and contribute to model development roadmap

Explore and segment content types

• Use clustering, principal component analysis, and other unsupervised methods to identify patterns in performance drivers and content types
• Experiment with GenAI to enrich data (e.g., augmenting metadata tagging or generating synthetic attributes)

Collaborate with business users to refine models and drive adoption

• Infuse models and model approach with users’ domain expertise and decision-making workflows
• Present early model outputs in accessible ways to solicit feedback and identify gaps, overlooked variables, and implicit assumptions from users
• Interpret 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 models

• Work with ML Engineers to deploy models in production, including API endpoints, and establish ML pipeline
• Contribute to shared libraries and modeling best practices across the data science team

Partner with product and platform teams to deliver impact

• Contribute to design and implementation of new products where data science models will be embedded, built by agile product PODs
• Collaborate with data architects, data engineers, and broader platform team to facilitate technical discussions and enrich the data available for data science

Must Have Skills / Requirements

• Proven experience as a Data Scientist
  1. 4+ years of experience
• Python and common ML library experience
  1. 4+ years of experience; (e.g., scikit-learn, XGBoost, pandas).
• Familiarity with AWS tools, especially SageMaker, or equivalent cloud-based ML environments
  1. 4+ years of experience

Preferred Requirements

• Experience in media & entertainment industry is a strong advantage but not required
• SQL fluency is a plus