Senior Programmatic Bidding Scientist - Huawei Petal Ads - Contractor

<h3><em>About Huawei</em></h3><p></p><p>Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We are committed to bringing digital to every person, home and organization for a fully connected, intelligent world.</p><p>At Huawei, we have two key drivers of innovation: science and technology, and customer needs. Both commercial value and market demands are driving our innovation and determining how we invest in science and technology. Breakthroughs in technology, in return, stimulate customer needs and allow us to create greater value for customers.</p><p></p><h3><em>About the IRC</em></h3><p>Huawei Ireland Research Centre's (IRC) mission is to position Huawei as a recognised technology leader and global information and communications technology (ICT) solutions provider. To achieve this, we are building an industry-recognised multi-disciplinary Research Centre of experts focusing on medium-term to long-term issues. The IRC will work closely with an open, innovative ecosystem with Huawei customers to address real-world issues. The IRC will also engage with key European universities to build a basic research capability to support Huawei technical projects.</p><h3><em>About Huawei Petal Ads</em></h3><p>Petal Ads is a smart marketing platform for Huawei devices. It provides marketing and traffic monetisation services for advertisers and publishers worldwide to help them achieve business growth and improve brand value. It does this by leveraging Huawei's "1+8+N" all-scenario ecosystem, Huawei apps' marketing capabilities, massive premium third-party traffic, and powerful ad technologies. Petal Ads has cooperated with advertisers spanning 200+ industries, while more than 60,000 apps worldwide have integrated Ads Kit. </p><h3><em>About the Job</em></h3><p></p><p>As a <strong>Senior Programmatic Bidding Scientist</strong>, you will be at the heart of our advertising engine, building the models and algorithms that power real-time programmatic bidding. You will work closely with our technical leads, senior scientists, and ML engineers to design, train, and optimise the models that drive performance in both our <strong>Ad Exchange (ADX)</strong> and third-party <strong>Supply-Side Platforms (SSPs)</strong>.</p><p>This role is ideal for a <strong>hands-on scientist</strong> with strong expertise in <strong>machine learning, optimisation, and deep learning</strong><strong>, and reinforcement learning (RL) </strong>who thrives on solving complex, data-driven problems and bringing cutting-edge models into production.</p><p></p><h3><em>Responsibility</em></h3><ul> <li><strong>Model Design &amp; Development</strong></li> <ul> <li>Design, implement, and iterate on real-time bidding (RTB) models and algorithms under the guidance of technical leads.</li> <li>Focus on building scalable, production-ready ML models for bidding and budget pacing.</li> <li>Leverage reinforcement learning to develop adaptive strategies that optimise long-term advertiser value and balance competing objectives (e.g., ROI, CTR, CVR, eCPM).</li> <li>Design feedback loops and reward functions that align model learning with advertiser and platform goals.</li> </ul> <li><strong>Algorithm Optimization</strong></li> <ul> <li>Continuously optimise bidding strategies to maximise campaign performance across diverse KPIs.</li> <li>Conduct deep analysis, simulations, and A/B testing to uncover new modelling opportunities and improve efficiency.</li> </ul> <li><strong>End-to-End Ownership</strong></li> <ul> <li>Take responsibility for the full lifecycle of bidding models: data preparation, training, evaluation, deployment, and debugging.</li> <li>Ensure model robustness, scalability, and stability in high-frequency, real-time environments.</li> </ul> <li><strong>Collaboration &amp; Delivery</strong></li> <ul> <li>Partner with engineering teams to ensure efficient deployment of models into production systems.</li> <li>Collaborate with technical leads and domain experts to translate strategic directions into concrete modelling solutions.</li> </ul></ul><ul> </ul><h3><em>Requirements</em></h3><ul> <li>Master’s or PhD in Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative discipline.</li> <li>Strong hands-on experience in <strong>machine learning model development and optimisation algorithms</strong> (e.g., regression, tree-based methods, deep learning, reinforcement learning, reinforcement learning).</li> <li>Proficiency in <strong>Python</strong> and ML frameworks such as <strong>PyTorch, TensorFlow, or Scikit-learn</strong>.</li> <li>Solid understanding of end-to-end ML system design: data pipelines, model training, validation, debugging, and optimisation.</li> <li>Strong analytical problem-solving skills, with the abi