The Role
Core is Ireland's largest marketing communications company. Core’s Data Practice helps brands maximize the impact of their marketing investments through cutting-edge data science and analytics.
As we continue to scale our advanced analytics capabilities, we are looking for a Head of Data Science - Marketing Measurement to lead and drive innovation in our marketing effectiveness practice. This role is both strategic and hands-on, requiring a leader who can develop best-in-class models while also building scalable tools that empower media planners and analysts across the organization.
The Role
As the Head of Data Science - Marketing Measurement, you will lead our marketing analytics function, developing and implementing advanced modelling techniques to measure and optimize media investment. You will be responsible for building Marketing Mix Models (MMM), lift experiments, discrete choice analysis, brand driver analysis, and other econometric and causal inference approaches.
In addition to delivering high-impact analytics projects, you will build applications and tools (leveraging primarily R, RShiny, RStan) that enable automation and self-serve capabilities for media planners and analysts.
You will collaborate closely with marketing strategists, data engineers, analysts, and business stakeholders to ensure that data-driven insights lead to better media allocation, higher ROI, and continuous innovation in marketing analytics.
What You’ll Do
1. Hands-on Model Development & Delivery
As we continue to scale our advanced analytics capabilities, we are looking for a Head of Data Science - Marketing Measurement to lead and drive innovation in our marketing effectiveness practice. This role is both strategic and hands-on, requiring a leader who can develop best-in-class models while also building scalable tools that empower media planners and analysts across the organization.
The Role
As the Head of Data Science - Marketing Measurement, you will lead our marketing analytics function, developing and implementing advanced modelling techniques to measure and optimize media investment. You will be responsible for building Marketing Mix Models (MMM), lift experiments, discrete choice analysis, brand driver analysis, and other econometric and causal inference approaches.
In addition to delivering high-impact analytics projects, you will build applications and tools (leveraging primarily R, RShiny, RStan) that enable automation and self-serve capabilities for media planners and analysts.
You will collaborate closely with marketing strategists, data engineers, analysts, and business stakeholders to ensure that data-driven insights lead to better media allocation, higher ROI, and continuous innovation in marketing analytics.
What You’ll Do
1. Hands-on Model Development & Delivery
- Develop and implement Marketing Mix Models (MMM) to measure the effectiveness of media investments using a Bayesian modelling approach.
- Design and execute lift experiments to validate marketing strategies.
- Use discrete choice modelling and brand driver analysis to understand consumer behaviour and brand impact.
- Continuously innovate on modelling techniques, incorporating causal inference, Bayesian approaches, and machine learning where applicable.
- Develop RShiny applications that allow media planners and analysts to run advanced marketing models independently.
- Work with our Data Technology team to integrate predictive models into our Snowflake-based data platform using Python and Streamlit.
- Automate marketing measurement workflows to improve efficiency and scalability.
- Establish frameworks for monitoring and validating marketing models over time.
- Stay at the forefront of marketing science, incorporating new methodologies, tools, and frameworks into our practice.
- Build a culture of experimentation and innovation, driving new ways to measure and optimize marketing.
- Translate complex analytical insights into clear, actionable recommendations for non-technical stakeholders.
- Act as a subject matter expert, mentoring and upskilling analysts and media planners on advanced modelling techniques.
- Partner with marketing, analytics, engineering, and product teams to ensure seamless integration of models into decision-making processes.
- Collaborate with leadership to define and drive the long-term marketing data science strategy.