Head of Data Science & Machine Learning Engineering

Resonate is a leading provider of high-quality, AI-powered consumer data, intelligence, and technology, empowering marketers to create a more personalized world that increases customer acquisition and lifetime value. Our SaaS platform, Ignite, and our Data-as-a-Service (DaaS) offerings provide unparalleled insights into consumer motivations, values, and behaviors, enabling our clients to connect with their target audiences in more meaningful and effective ways. We are a dynamic and fast-growing company seeking passionate and innovative individuals to join our team!

We are seeking a visionary and hands-on leader to become our Head of Data Science and Machine Learning Engineering. This pivotal role provides a unique opportunity to own the entire AI/ML lifecycle, from initial research and algorithmic innovation to robust, scalable production deployment. You will lead our talented Data Science (DS) and Machine Learning Engineering (MLE) teams, fostering a unified culture of excellence and accountability. As a key technology leader, you will be responsible for both setting the strategic AI vision and ensuring its flawless execution, directly impacting our product, customers, and competitive edge. 

The ideal candidate will have proven experience leading and managing both data science (research-focused) and machine learning engineering (production-focused) teams. They will demonstrate a strong track record of owning the entire machine learning lifecycle, including the successful deployment and ongoing maintenance of models in large-scale, real-time production environments. Experience in consumer data, ad-tech, or mar-tech industries will be considered a strong plus. 

In this role, you be at the forefront of extracting valuable insights from a vast array of online and offline data signals. You will drive innovation by developing a machine learning interface that leverages the power of foundation models to solve a myriad of tasks in predictive analytics – segmentation, forecasting, and classification. This is a unique opportunity to be at the forefront of building the next generation of enterprise level machine learning systems.  

Your expertise will contribute to solving complex, industry-specific problems across health, finance, consumer goods, politics, and advocacy. Domain-specific experience in any of these areas is a plus, as it helps us better understand unique market challenges and craft targeted machine learning solutions.  At Resonate, we foster a culture of innovation and expect you to play an integral part in advancing our product suite, spanning from data development to software-as-a-service (SaaS) tools. You will be encouraged to challenge the status quo, introduce new tools and techniques, and bring forward fresh ideas that drive our mission forward.   

 If you are passionate about data, possess a keen eye for detail, and have an unwavering commitment to innovation, we invite you to join our team and help shape the future of our company.   

Key Responsibilities: 

Team Leadership: 

• Lead, manage, and mentor our integrated Data Science and Machine Learning Engineering teams ensuring full accountability for both methodology and delivery.
• Foster a highly collaborative environment where data scientists and MLEs work seamlessly to accelerate the path from idea to production value.
• Define the operational model for the combined team to optimize for velocity, quality, and innovation, even with a lean team structure. 

 End-to-End Strategic Ownership: 

• Drive the strategic vision for data science and AI, ensuring alignment with our product roadmap and business goals.
• Take full ownership of the end-to-end machine learning lifecycle, from model ideation and development to deployment, monitoring, and maintenance in a production environment.
• Propose, lead, and communicate an R&D agenda to advance our product lines, with a focus on methodologies, modeling techniques, and agentic systems. 

 Technical and Operational Delivery: 

• Drive the architectural vision for our MLOps infrastructure, working with the MLE team to install and champion best practices for scalable, automated, and robust model deployment.
• Provide hands-on leadership in the development and deployment of advanced machine learning models, including deep learning techniques, embeddings, neural networks, and GNNs.
• Leverage yo