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Sony Pictures Entertainment

Sony Pictures Entertainment

www.sonypictures.com

2 Jobs

9,762 Employees

About the Company

Sony Pictures Entertainment (SPE) is a subsidiary of Tokyo-based Sony Group Corporation. SPE's global operations encompass motion picture production and distribution; television production and distribution; digital content creation and distribution; worldwide channel investments; home entertainment acquisition and distribution, operation of studio facilities; development of new entertainment products, services and technologies; and distribution of filmed entertainment in more than 130 countries.

Listed Jobs

Company background Company brand
Company Name
Sony Pictures Entertainment
Job Title
Data Scientist II, AI Focus
Job Description
**Job Title**: Data Scientist II, AI Focus **Role Summary** Apply generative AI, large language models (LLMs), and advanced machine learning to tackle media‑industry challenges. Develop, deploy, and monitor predictive and generative models that inform production, distribution, and marketing decisions, while championing data‑driven insights across the organization. **Expectations** - 6+ years of machine learning or data science experience, with a focus on applied modeling. - Deep expertise in generative AI (LLM prompt engineering, fine‑tuning) and traditional predictive analytics. - Proven ability to advance models from prototype to production, ensuring performance and scalability. - Strong stakeholder collaboration, translating complex analyses into actionable business recommendations. **Key Responsibilities** - Design, implement, and fine‑tune LLM‑based solutions for text analysis, summarization, metadata enrichment, and content tagging. - Research and prototype agentic AI frameworks to automate data workflows. - Build predictive models and advanced analytics that guide creative and business strategy. - Cleanse, transform, and extract features from large, unstructured datasets for insight generation. - Partner with engineering teams to MLOps‑ready model deployment (containerization, workflow orchestration, monitoring). - Create compelling visualizations and reports for technical and non‑technical audiences. - Collaborate with cross‑functional partners (marketing, distribution, finance) to translate insights into actions. - Stay current on emerging ML techniques, maintaining SPE’s competitive edge in AI capabilities. **Required Skills** - Python (advanced), SQL (proficient). - Generative AI (LLM, prompt engineering, fine‑tuning); familiarity with Hugging Face, LangChain, or similar libraries. - Statistical modeling, predictive modeling, variable importance, and model interpretability. - MLOps practices: model lifecycle management, containerization (Docker), workflow orchestration (Airflow, Kubeflow). - Strong communication skills with ability to explain complex concepts to stakeholders. - Analytical mindset, results orientation, excellent organization, and attention to detail. **Required Education & Certifications** - Bachelor’s degree in a quantitative discipline (Statistics, Computer Science, Engineering, Mathematics). - Advanced degree (Master’s or Ph.D.) is a plus. - No specific certifications required, though familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, Azure ML) is advantageous.
Culver city, United states
Hybrid
Mid level
19-11-2025
Company background Company brand
Company Name
Sony Pictures Entertainment
Job Title
Dir. Data Science
Job Description
Job Title: Director of Data Science Role Summary: Lead a high‑performing data science team, design and operationalize end‑to‑end machine learning solutions for content, marketing, and distribution, and maintain technical excellence and governance across the organization. Expectations: - 10+ years in data science, machine learning or applied analytics roles. - 3+ years of people management with hiring, mentoring and performance oversight. - Advanced proficiency in Python, SQL, scikit‑learn, XGBoost, TensorFlow or PyTorch. - Deep expertise in MLOps: CI/CD for ML, feature stores, model registries, monitoring, drift detection, and cloud platforms (AWS, GCP). - Proven delivery of complete ML pipelines with measurable business impact. - Strong knowledge of traditional ML, generative AI (prompt engineering, embeddings, RAG, vector databases, conversational AI). - Excellent communication, storytelling, and influence skills across all levels. - Ability to translate ambiguous business requests into structured, actionable projects. Key Responsibilities: - Architect and deploy machine learning models, including deep learning and generative AI where relevant. - Oversee all phases: problem scoping, data exploration, feature engineering, modeling, validation, and production deployment. - Conduct code reviews, set technical standards, and enforce model quality, reproducibility, and performance monitoring. - Guide proof‑of‑concept development, validate feasibility, and partner with engineering for productionization. - Work with product teams to define requirements, drive adoption, measure impact, and iterate data science products. - Promote responsible AI practices: interpretability, fairness assessments, and ongoing governance. - Manage, mentor, and grow a team of data scientists and analysts, fostering a collaborative, learning‑oriented culture. - Transform loosely defined business asks into prioritized, deliverable projects with clear roadmaps. - Serve as a strategic advisor to stakeholders, articulating data science value and uncovering actionable insights. Required Skills: - Programming: Python, SQL, scikit‑learn, XGBoost, TensorFlow, or PyTorch. - MLOps: CI/CD pipelines, Docker/K8s, feature stores, model registries, monitoring, drift detection. - Cloud: AWS, GCP (or equivalent). - Generative AI: prompt engineering, embeddings, RAG, vector databases, conversational agents. - Leadership: team management, mentoring, performance management, stakeholder communication. - Responsible AI: fairness, interpretability, governance. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field. - Relevant certifications preferred: AWS Certified Machine Learning – Specialty, Google Cloud Professional Data Engineer, or similar.
Culver city, United states
On site
Senior
10-12-2025