Required Skills & Experience
- 6+ years professional experience in Data Science, Machine Learning, or Applied AI.
- Highly proficient with Snowflake, Airflow, and DBT for data modeling
- Experience with MLOps, including model deployment, versioning, monitoring, and productionization.
- Strong hands-on experience using Python and SQL for data analysis, modeling, and machine learning. ○ Strong understanding of statistics, predictive modeling, feature engineering, model validation, and experimentation.
- Experience working alongside Data Engineering teams and understanding how data pipelines, transformations, and modeling impact downstream ML solutions.
- Strong understanding of data quality, including the ability to identify gaps or issues that could negatively impact model performance.
Nice to Have Skills & Experience
- Familiarity with dbt / dbt Cloud and modern data transformation workflows.
- Experience developing or integrating generative AI, LLM, or agentic AI solutions.
- Understanding of AI governance, model risk, data privacy, or responsible AI practices.
- Experience working within a data organization undergoing a transition from traditional BI/reporting toward AI/ML-driven products.
- Experience within entertainment, media, content protection, cybersecurity, or another highly governed data environment.
Job Description
An entertainment client based in Burbank, CA is looking for a Sr. Data Scientist to join the Studios organization. The Content Security data platform and AI team is evolving from a historically dashboard and reporting-focused organization into a more advanced data and AI function. The team currently supports data engineering, data platforms, analytics, and data governance, while expanding its capabilities around artificial intelligence, machine learning, and agentic AI. The Senior Data Scientist will play a key role in this evolution by identifying and developing AI/ML use cases, building data-driven solutions, and partnering closely with Data Engineers to ensure the underlying data is reliable, governed, secure, and ready for AI applications. This person should be comfortable operating in an environment where the data foundation is actively maturing and where opportunities exist to help define how data science and AI capabilities are implemented across the organization.
Day-to-Day Responsibilities
- Partner with Data Engineering, platform, and business stakeholders to identify opportunities where machine learning, AI, and advanced analytics can solve business and operational challenges.
- Design, develop, test, and evaluate machine learning models and data science solutions.
- Help transition the organization from traditional dashboards and descriptive reporting toward predictive, intelligent, and AI-enabled solutions.
- Explore and prototype AI and agentic AI use cases leveraging the team's enterprise data.
- Work closely with Data Engineers to identify the datasets, pipelines, transformations, and data models required for ML and AI use cases.
- Perform exploratory data analysis, feature engineering, statistical analysis, and model evaluation.
- Assess data quality and determine whether datasets are sufficiently complete, accurate, and structured for downstream AI/ML applications.
- Partner with the broader team around data governance, security, and responsible use of enterprise data within AI solutions.
- Help establish best practices for taking data science solutions from experimentation and proof of concept toward scalable production environments.
- Communicate technical findings, model performance, risks, and recommendations to both technical and non-technical stakeholders.
- Evaluate emerging AI/ML approaches and determine where they can provide practical value to Content Security.