Data Scientist

Job Title: Data Scientist Location: California, Burbank (Hybrid role – 3 days on-site) A Senior Data Scientist job description involves leading complex analytics projects, developing advanced AI/ML models (like generative AI), mentoring junior staff, and translating technical insights into strategic business actions for stakeholders, 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. 1. Ability to translate complex technical requirements into clear non-technical updates for executives. a. 8+ years of experience. 1. Proven experience with analyzing complex datasets to uncover trends and generate recommendations – Strategic Insights a. 10+ years of experience. Technology Requirements: 1. Strong skills in Python/R, SQL, and advanced ML (recommendation systems, time-series, Bayesian methods, simulation). 1. Experience building MLOps (deployment, monitoring, governance) and working with cloud data stacks (BigQuery/Snowflake, AWS/GCP). 1. Experience with AWS cloud and Analytics (BI) tools (Tableau, Power BI).