Title: Data Scientist IV
Work Location: Burbank CA - 3 days on-site.
Job Responsibilities / Typical Day in the Role
Develops and maintains the data science vision & roadmap for our studio business units, primarily Theatrical and Content Sales.
Lead complex analytics project and develop advanced AI/ML models
Lead and grow a team of Data Scientists, establishing best practices in experimentation, causal inference, and MLOps (Machine Learning Operations).
Translate technical insights into strategic business actions for stakeholders
Drive data-driven business decision-making for revenue optimization.
Drive experimentation at scale (A/B, multivariate, adaptive methods like multi armed bandits) and codify guardrails for metrics, lift, and governance across product surfaces.
Build production grade models (predictive, NLP, CV, generative) and pipelines for recommendations, classification, content valuation, and forecasting; enforce model monitoring and responsible AI.
Develop predictive models for Sales Planning and forecasting
Partner with Finance & Content Sales to operationalize models into decision workflows; deliver dashboards and executive-ready narratives.
Design and scale greenlight frameworks: integrate sales demand signals, competitive intelligence, and financial risk metrics.
Operationalize data: define high quality feature stores, curate canonical datasets (viewing, engagement, metadata, rights), and ensure privacy, lineage, and compliance.
Ensure governance and compliance: data lineage, privacy, and responsible AI in financial modeling.
Communicate impact to executives with clear narratives, dashboards, and decision memos; translate complex analyses for non-technical audiences.
Must Have Skills / Requirements
1) Experience designing, implementing, and validating sophisticated ML algorithms and models.
a. 10+ years of experience.
2) Ability to translate complex technical requirements into clear non-technical updates for executives.
a. 8+ years of experience.
3) Proven experience with analyzing complex datasets to uncover trends and generate recommendations Strategic Insights
a. 10+ years of experience.
Nice to Have Skills / Preferred Requirements
1) Background in content valuation, ad decisioning/forecasting, or growth analytics for media products.
2) Experience with adaptive experimentation (bandits), generative AI, multimodal models, or semantic search in media workflows.
3) Familiarity with media supply chain (metadata, rights, distribution) and privacy/identity (audience modeling, identity graphs). Soft Skills:
1) Expertise in financial modeling, forecasting, and optimization for content economics.
2) Proven ability to align stakeholders across Product, Engineering, Marketing, Content, Licensing and Sales Planning;
3) Exceptional communication skills for executive stakeholders. Technology Requirements:
1) Strong skills in Python/R, SQL, and advanced ML (recommendation systems, time-series, Bayesian methods, simulation).
2) Experience building MLOps (deployment, monitoring, governance) and working with cloud data stacks (BigQuery/Snowflake, AWS/Google Cloud Platform).
3) Experience with AWS cloud and Analytics (BI) tools (Tableau, Power BI). Education / Certifications
1) None required. Interview Process / Next Steps
1) 1st round with HM (30-min screening)
2) 2nd round with Peer Data Scientist