As the Manager, Data Science, you will support the delivery of Google Meridian MMM projects and other data science engagements for Brainlabs clients, working closely with the Director of Data Science to produce technically rigorous, clearly communicated outputs. You are responsible for the quality of your own modelling work and for helping clients understand what the analysis means for their media decisions. This is a role for a data scientist who is strong on the technical fundamentals, curious about how marketing data can drive better business decisions, and developing the skills to communicate complex ideas clearly.

What you do

• Support MMM Project Delivery: You contribute to the delivery of Google Meridian and other MMM projects, owning specific workstreams including data preparation, model runs, and scenario analysis under the direction of the Director of Data Science.
• Deliver Other Modelling Projects: You support and independently deliver a range of data science engagements, applying statistical and analytical skills to real client problems with a focus on accuracy and clear interpretation.
• Translate Outputs Into Insight: You take model outputs and draft clear, accessible summaries and narratives that connect findings to media budget decisions, ready for review and client presentation.
• Apply AI to Data Science Workflows: You use Claude and other AI tools as a standard part of your workflow, finding practical ways to accelerate code development, documentation, and output communication.
• Contribute to Practice Development: You support the development of Brainlabs' data science capability through documentation, process improvement, and sharing what you learn across the team.

Who you are

• A Rigorous and Curious Data Scientist: You have hands-on experience with Marketing Mix Modelling or related statistical modelling, including working knowledge of Meridian, Robyn, and/or PyMC, and you care deeply about getting the analysis right — not just delivering an output.
• Technically Proficient: You are experienced in Python and comfortable working with GCP, with a solid understanding of Bayesian statistics and marketing attribution concepts.
• A Practical AI User: You use AI tools in your day-to-day work, with a habit of exploring how they can improve your outputs or speed up your workflow.
• Developing as a Communicator: You are building your ability to explain technical concepts clearly to non-technical audiences, and take feedback on how to make your outputs more accessible.
• Detail-Oriented: You take pride in the accuracy and rigour of your work, and apply a consistent quality check to everything you deliver.
• Curious and Motivated: You are genuinely interested in the intersection of data science and marketing effectiveness, and proactively develop your skills beyond what the immediate job requires.

How you succeed

• Modelling Quality: The workstreams you own within MMM and other projects meet the quality standard set by the Director, with outputs that are accurate, well-documented, and reproducible.
• Clear Output Communication: The summaries and narratives you draft require minimal revision before client presentation, and you can explain your methodology clearly when asked.
• AI Adoption: You can demonstrate at least one documented AI application per month that improved your workflow or the quality of your output.
• Delivery Reliability: You hit agreed deadlines on your workstreams and raise risks early when timelines are at risk.
• Practice Contribution: You contribute at least one improvement or piece of documentation to the data science team each quarter, evidenced by adoption or feedback from the Director.