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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Paramount Global - **Location:** Burbank, CA, United States - **Experience:** Starter - **Salary:** $99,000.0 - $140,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, BigQuery, Code Review, Data Intelligence, Python (Programming Language), Machine Learning, SQL Databases, Google Cloud, Model Validation, Information Technology, User Administration, Unsupervised Learning - **Published:** September 3, 2026 - **Apply:** https://www.nexxt.com/job.asp?id=3375525995&tx=JJ5145FFF&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role A solid foundation in Python and SQL Ability to translate business problems into data problems Comfort writing production-quality code in a collaborative environment. Clear communication with technical and non-technical stakeholders through concise storytelling and visualizations that translate findings into actionable insights. Judgment to balance technical rigor with functional usability and business adoption. A willingness to continuously learn new tools and techniques., 0-2 years of experience in Data Science and ML Engineering. MS in Statistics, Data Science, Computer Science, or related discipline preferred; or equivalent professional industry experience. Experience with supervised and unsupervised learning methodologies. Experience with data exploration, transformation, and model development, with exposure to productionizing and monitoring. Strong data fluency: selecting the right inputs, engineering business-relevant features, and validating that findings are reliable. Familiarity with core statistical/ML methods and model validation fundamentals. Concise and influential communication skills for a wide variety of stakeholders. Ability to produce clear technical documentation and stakeholder presentations. Strong attention to detail with a penchant for data accuracy. Must successfully pass a background check. You might also have Experience using Google Cloud Platform (BigQuery, ML Engine, and APIs). Experience with integrating AI solutions into existing business processes. ## Description We are seeking a Data Scientist for this entry-level role. You will work to support the team in building ML-powered analyses and products that shape business strategy, optimize content, inform marketing investment, and enhance the user experience. You will leverage rich datasets such as video and ad consumption, clickstream activity, subscription history, and 2nd/3rd-party data to build user- and session-level causal and predictive models., Translate complex business questions into clear problem statements, success metrics, and actionable quantitative solutions. Use an iterative approach: start with quick, decision-useful analysis, then refine based on feedback and observed impact. Implement and maintain reliable ML/analytics pipelines, partnering with engineering as needed to productionize and monitor. Contribute to delivering clear, impactful insights to stakeholders. Collaborate across the Product organization to operationalize data science solutions that inform strategy and optimize the user experience. Contribute to data science and product analytics best practices through documentation, code reviews, and knowledge sharing. Key Projects Leverage 1st / 2nd / 3rd party data to build global models that predict user behavior throughout their subscription journey (e.g., sign-up, churn) Build models to identify and measure high-value user actions and drivers of habit formation. Develop session-level predictions to uncover user intent at the start of a session. Build models to predict content viewership and identify content traits that resonate most with each subscriber. Create user segmentations that enable meaningful cohort-based targeting and support near- personalized experiences. Perform diagnostic analyses such as evaluation of failed searches to surface opportunities for product improvement. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Are Code Reviews Worth It? Insights from 16 Years of Review Data](https://www.wearedevelopers.com/videos/1135-are-code-reviews-worth-it-insights-from-16-years-of-review-data) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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