Senior Product Manager, Modeling & Machine Learning Operations

Zeta Global

23d•$150,000 - $190,000•Remote

About The Position

At Zeta Global, we are spearheading innovations in data-driven marketing, leveraging advanced machine learning and AI to deliver unparalleled insights and performance. We are seeking a visionary Senior Product Manager to lead our Machine Learning Operations initiatives, focusing on developing retail-specific models and a user-friendly Model Workbench that empowers marketers to harness the power of Machine Learning without the need for deep technical expertise. Job Description: Machine Learning Operations Leadership: Spearhead the development and maintenance of robust ML Ops processes to streamline model deployment, monitoring, and management. Retail Model Innovation: Design and refine machine learning models tailored to the retail industry, enhancing our predictive capabilities and market understanding. Model Workbench Development: Lead the creation of a Model Workbench platform that enables marketers to easily interact with and utilize machine learning models, incorporating user-friendly interfaces and tools. Customer-Centric Product Development: Ensure all product development is guided by a deep understanding of customer needs and market demands, delivering solutions that are both intuitive and powerful. Agentic Infrastructure Integration: Work towards integrating traditional ML with advanced generative models, focusing on explainability, actionable recommendations, and recursive training based on user interactions.

Requirements

Experience in Product Management: Proven track record of successful product management, ideally in a technology-focused environment.
Expertise in Machine Learning: Strong understanding of ML Ops practices, with experience in developing and managing Machine Learning models, particularly for retail applications.
Technical Proficiency: Comfortable working with both traditional and generative machine learning technologies, with a keen insight into model explainability and user interaction.
Strategic Thinking: Ability to think strategically about product development, integrating customer insights and market trends into actionable product features.
Communication Skills: Excellent communication skills with the ability to collaborate effectively across cross-functional teams and articulate product visions clearly to both technical and non-technical stakeholders.
Background in Retail Analytics: Direct experience or a strong understanding of the retail industry's data analytics needs.
Familiarity with Agentic Infrastructure: Knowledge of combining traditional ML models with generative models to enhance user interaction and model training.

Responsibilities

Machine Learning Operations Leadership: Spearhead the development and maintenance of robust ML Ops processes to streamline model deployment, monitoring, and management.
Retail Model Innovation: Design and refine machine learning models tailored to the retail industry, enhancing our predictive capabilities and market understanding.
Model Workbench Development: Lead the creation of a Model Workbench platform that enables marketers to easily interact with and utilize machine learning models, incorporating user-friendly interfaces and tools.
Customer-Centric Product Development: Ensure all product development is guided by a deep understanding of customer needs and market demands, delivering solutions that are both intuitive and powerful.
Agentic Infrastructure Integration: Work towards integrating traditional ML with advanced generative models, focusing on explainability, actionable recommendations, and recursive training based on user interactions.