Senior Data Scientist

𝗝𝗼𝗯 𝗧𝗶𝘁𝗹𝗲: Senior Data Scientist 𝗝𝗼𝗯 𝗟𝗼𝗰𝗮𝘁𝗶𝗼𝗻: New York 𝗝𝗼𝗯 𝗧𝘆𝗽𝗲: Long-Term Contract 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗟𝗲𝘃𝗲𝗹: Senior (7–12+ Years) 𝗧𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Our client is seeking a Senior Data Scientist with deep experience in graph databases, ad delivery systems, and large-scale digital content platforms. This role is ideal for a data science leader who has worked within streaming media ecosystems and understands the complexities of ad-supported digital content delivery at scale. You will partner closely with Engineering, Product, and Ad Technology teams to design and deploy advanced data models that power targeting, delivery optimization, content relationships, and monetization strategies. Your work will directly influence how millions of users experience digital content across streaming, web, and connected TV platforms. 𝗧𝗼𝗼𝗹𝘀 & 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 • 𝗗𝗮𝘁𝗮 & 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴: Python, SQL, Jupyter, ML frameworks • 𝗚𝗿𝗮𝗽𝗵 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀: Neo4j, Amazon Neptune, or similar • 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Cloud data warehouses and analytics platforms • 𝗔𝗱 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀: Digital advertising and content analytics tools • 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Jira, Confluence, Slack, Microsoft Teams 𝗥𝗼𝗹𝗲𝘀 & 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 • Design, develop, and deploy advanced data science models to support digital content and advertising delivery • Apply graph-based modeling to represent and analyze relationships between users, content, ads, devices, and delivery contexts • Build algorithms that improve ad targeting, frequency management, yield optimization, and delivery efficiency • Leverage large-scale behavioral and event data to generate actionable insights and predictive models 𝗚𝗿𝗮𝗽𝗵 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 & 𝗗𝗮𝘁𝗮 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 • Design and implement graph data models using technologies such as Neo4j, Amazon Neptune, or similar platforms • Optimize graph queries for performance, scalability, and real-time use cases • Collaborate with data engineering teams to integrate graph data stores into broader data platforms and pipelines • Translate complex relationship-driven problems into scalable graph-based solutions 𝗔𝗱 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 & 𝗠𝗼𝗻𝗲𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 • Partner with AdTech and Product teams to analyze ad delivery performance across streaming and digital platforms • Develop models and metrics to evaluate inventory utilization, fill rates, latency, and ad relevance • Support experimentation and A/B testing related to ad formats, targeting strategies, and delivery logic • Provide data-driven recommendations to improve monetization outcomes while maintaining high-quality user experiences 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 & 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 • Analyze user engagement and content consumption patterns across streaming and digital platforms • Develop models that connect content metadata, viewing behavior, and advertising performance • Support personalization, recommendation, and discovery initiatives through advanced analytics • Ensure data science solutions scale across high-traffic, real-time content delivery environments 𝗖𝗿𝗼𝘀𝘀 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 • Serve as a senior data science partner to Engineering, Product, and Business stakeholders • Communicate complex analytical concepts and results in clear, business-ready language • Mentor junior data scientists and promote best practices across the data organization • Influence data strategy, tooling, and architectural decisions at the platform level 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 𝗠𝘂𝘀𝘁 𝗛𝗮𝘃𝗲 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 • 7–12+ years of experience in Data Science, Applied Machine Learning, or Advanced Analytics • Hands-on experience with graph databases and graph-based modeling for production use cases • Strong background in ad delivery, ad tech, or advertising analytics • Experience working on digital content delivery platforms at scale • Prior experience in streaming media organizations (e.g., Hulu, Disney+, Netflix, Amazon Prime Video, Roku, similar) • Strong proficiency in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, TensorFlow) • Experience working with large, complex datasets and real-time or near-real-time data systems • Ability to translate business problems into scalable analytical and machine learning solutions 𝗣𝗿𝗲𝗳𝗲𝗿𝗿𝗲𝗱 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 • Experience with connected TV (CTV) or ad-supported streaming platforms • Familiarity with recommendation systems, personalization, or content discovery models • Experience working with cloud-based data platforms (AWS, GCP, or Azure) • Knowledge of experimentation frameworks and causal inference techniques • Experience collaborating with distributed engineering and data teams • Strong storytelling and executive-level communication skills