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Senior Product Manager – Ssp – AI and Data Science
| Company | Nexxen |
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| Location | Bellevue, WA, USA |
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| Salary | $160000 – $210000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s |
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| Experience Level | Senior |
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Requirements
- 5+ years of technical product management experience, including direct ownership of AI/ML product features
- Experience with ad tech platforms, ideally with exposure to SSPs, RTB protocols, and programmatic media
- Deep understanding of machine learning lifecycle: data collection, feature engineering, model training, deployment, monitoring
- Demonstrated experience working with data science and ML engineering teams in a cross-functional agile environment
- Bachelor’s degree in Computer Science, Engineering, or a related technical field; an advanced degree or MBA is a plus
- Knowledge of common ML frameworks (e.g., TensorFlow, PyTorch, XGBoost) and data platforms (e.g., Snowflake, Spark, Airflow)
- An analytical mindset with the ability to translate business problems into technical solutions
- Strong leadership and communication skills with a track record of influencing cross-functional teams and executive stakeholders
- Experience driving data-informed decisions through metrics, experimentation, and customer feedback
Responsibilities
- Deeply understand the needs of our business and customers to define resilient, intelligent, and scalable product solutions
- Champion the discovery, definition, and prioritization of AI and ML features that enable better yield optimization, traffic prediction, and fraud detection
- Collaborate closely with engineering and data science teams to evaluate the feasibility and impact of machine learning approaches
- Define product requirements, success metrics, and milestones specifically tailored for AI-powered features
- Work with ML teams to operationalize models, including A/B testing frameworks, model retraining pipelines, and feedback loops
- Identify and quantify long-term opportunities for machine learning and AI technologies to differentiate our SSP in the market
- Ensure AI/ML models are explainable, ethical, and aligned with customer and business needs
- Drive alignment across executive stakeholders by clearly communicating technical concepts and business value
- Partner with data engineering and DevOps to ensure data quality, monitoring, and deployment pipelines support high-performing AI systems
Preferred Qualifications
- Prior experience in building AI-powered features such as traffic forecasting, content classification, anomaly detection, or recommendation systems
- Familiarity with real-time data processing pipelines and MLOps best practices
- Experience navigating the ethical and regulatory implications of deploying AI at scale
