Head of Data Science

Head of Data Science at PMG leads AI/ML strategy and drives data-driven decisions across marketing, media, and business outcomes. Our Data Science team transforms complex data into strategic insights, building predictive models, automation, and AI-driven solutions that help brands optimize performance, personalize experiences, and maximize impact across digital channels. You’ll collaborate with engineers, analysts, media strategists, and product teams to apply advanced data science techniques to enhance targeting, improve measurement, and develop next-generation marketing intelligence.

Whether it’s training machine learning models, engineering scalable data pipelines, fine-tuning optimization algorithms, or advancing AI-driven marketing strategies, your expertise will help brands connect with the right audiences, at the right time, with the right message—more efficiently than ever before. Beyond execution, you’ll play a key role in exploring emerging AI technologies, refining data science methodologies, and shaping the future of predictive analytics and automation.

You’ll have opportunities to test new approaches to measurement, integrate deep learning into decision-making processes, and experiment with AI-powered media solutions that redefine what’s possible in digital marketing. At PMG, we don’t just respond to industry trends—we set them, ensuring our clients stay ahead in a rapidly evolving, data-driven world. As Head of Data Science, you’ll have the opportunity to tackle complex challenges, lead AI-driven innovation, and turn analytics into meaningful business and marketing outcomes.

• Develops and champions the long-term (3-5 year) strategic vision and execution roadmap for a broad data science organization, ensuring alignment with PMG’s overarching business strategy and market leadership goals.
• Leads and mentors a team of Data Science Directors and/or Senior Managers, fostering a culture of high performance, strategic thinking, innovation, and impactful leadership across multiple teams.
• Accountable for the P&L or substantial budget of a large data science practice, driving revenue growth, cost efficiencies, and measurable ROI from AI/ML initiatives.
• Directs the incubation, scaling, and enterprise-wide adoption of cutting-edge AI/ML capabilities (e.g., federated learning, large-scale reinforcement learning, advanced knowledge graphs) that create significant competitive differentiation.
• Serves as a primary advisor to C-suite executives on AI/ML strategy, investment, and risk, translating complex technological possibilities into clear business implications and strategic opportunities.
• Builds and cultivates C-level relationships with key clients and strategic partners, acting as an executive sponsor for critical data science engagements and driving new business at a strategic level.
• Establishes and governs enterprise-level policies for AI ethics, data governance, model risk management, and regulatory compliance, ensuring responsible and secure AI deployment at scale.
• Represents PMG's AI/ML thought leadership and capabilities at premier industry events, in influential publications, and with key industry analysts, shaping market perceptions and attracting top talent.
• Drives organizational design, talent strategy, and succession planning for a significant segment of the data science function, ensuring a robust pipeline of future leaders and technical experts.
• Oversees the most critical and complex AI/ML programs, ensuring they deliver transformative business outcomes and set new standards for excellence in execution.
• Stay current with emerging data science–focused Python libraries and apply them effectively to develop models and business-impactful solutions.

• 20+ years of experience in data science, including 10+ years of leadership experience, with a bachelor;s degree or equivalent work experience.
• Proven ability to lead and scale data science programs across complex organizations, translating strategic objectives into high-impact analytical initiatives.
• Deep expertise in machine learning, causal inference, and statistical modeling using Python, R, and advanced…