Applied AI Scientist III
- Lead AI innovation by identifying and testing opportunities to integrate advanced generative AI and other ML methods, including agent-based systems, into SEM and Metasearch workflows
- Design, develop and deploy AI solutions to improve bidding, capital allocation, audience targeting, creative optimisation and campaign segmentation through structured test-and-learn approaches
- Develop and implement prompt engineering, tool integrations and orchestration strategies for autonomous AI workflows
- Rapidly prototype proof-of-concepts to assess value before scaling solutions into production
- Execute A/B and multivariate tests, applying statistical methods such as t-tests, confidence intervals and distributions to ensure results are valid and repeatable, and improving experimental design for marketing applications
- Apply generative AI, reinforcement learning and other ML techniques to improve operational efficiency and campaign outcomes through automation and scalability
- Implement monitoring, observability and guardrails for AI systems to ensure performance, reliability, compliance and safety
- Identify and address algorithm risks or inefficiencies before they impact marketing performance
- Collaborate with Marketing, Engineering, Science and Product teams to align AI innovations with business goals and scale them across brands, products and marketing processes
- Partner with product and engineering teams to design and enhance APIs, dashboards and bidding tools that embed AI capabilities into SEM and Metasearch operations
- Analyse large-scale SEM and Metasearch datasets, identify changes in market dynamics such as seasonality, auction changes and competitor actions, and implement strategies to improve ROI and competitive positioning
- Build pipelines, workflows and tools for continuous learning and improvement from AI-driven initiatives, and troubleshoot issues including data quality problems, pipeline failures and degraded model performance
- Ensure responsible AI practices by addressing bias, fairness, privacy and transparency in AI solutions
- Present recommendations and results to senior leadership in a clear, compelling and business-relevant way
- Bachelor's or Master's in Computer Science, Data Science, AI/ML, Statistics or a related quantitative field; PhD preferred
- Hands-on experience with generative AI methods, deep learning, natural language processing or reinforcement learning
- Proven track record applying AI and ML to solve complex business problems, ideally in marketing, advertising or e-commerce
- Strong proficiency in Python (PyTorch, TensorFlow, scikit-learn), SQL and cloud ML orchestration environments such as AWS, Databricks or Flyte
- Experience with search marketing, ad auctions, bidding optimisation or customer segmentation is a plus
- Skilled in rapid prototyping, hypothesis testing and iteration toward production-ready solutions
- Experience applying statistical testing methods to marketing experiments, including A/B testing and test readouts
- Able to design, monitor and maintain autonomous AI systems with appropriate safety and compliance measures
- Able to troubleshoot operational AI issues and work with cross-functional teams to resolve them quickly
- Strong communicator who can translate complex AI concepts into insights for both technical and non-technical audiences
- Self-starter who proactively identifies opportunities to leverage AI for measurable business impact
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