Huawei Petal Ads – Senior Programmatic Bidding Scientist - Contractor

About Huawei

Huawei’s products and services are available in more than 170 countries and are used by a third of the world’s population. Huawei Consumer Business Group (CBG) is one of Huawei’s three business units and covers smartphones, PCs and tablets, wearables and cloud services etc. Huawei Consumer BG is the leader of all-scenario AI life. It covers smartphones, PC and tablets, wearables, mobile broadband devices, family devices and device cloud services. Huawei Consumer BG is dedicated to delivering the latest technologies to consumers and sharing the happiness of technological advances with more people around the world. Walk the walk and make dreams come true.

About the IRC

Huawei Ireland Research Centre's (IRC) mission is to position Huawei as a recognized technology leader and global information and communications technology (ICT) solutions provider. To achieve this we are building an industry-recognized multi-discipline 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.

About Huawei Petal Ads

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. 

About the Job

As a Senior Programmatic Bidding Scientist, you will be a key player in the engine room of our advertising platform. You will apply your deep understanding of machine learning, statistical modelling, and optimisation to design, build, and refine the high-frequency bidding algorithms. Working within our Ad Exchange (ADX) and bidding to third-party Supply-Side Platforms (SSPs), your work will directly impact the performance and efficiency of our programmatic advertising capabilities. We keen to have a hands-on problem-solver with a passion for building and debugging complex, data-driven systems to join the team.

Responsibility

• Design, implement, and iterate on real-time bidding (RTB) strategies and algorithms within our programmatic environment.
• Focus on the continuous optimisation of our bidding and budget pacing algorithms to maximise campaign performance against various KPIs.
• Conduct in-depth analysis, modelling, and simulation to identify opportunities for algorithmic improvements.
• Take ownership of the end-to-end lifecycle of bidding models, including design, implementation, testing, and debugging in a production environment.
• Collaborate with engineering teams to ensure the robust and scalable implementation of your bidding algorithms.

Requirements

• A Master's or PhD in a quantitative field such as Computer Science, Statistics, Machine Learning, or a related discipline.
• Strong, hands-on experience in designing and implementing machine learning models and optimisation algorithms.
• Proficiency in programming languages commonly used in data science, such as Python, and familiarity with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• A solid understanding of the principles of modelling, design, implementation, debugging, and optimisation of complex software systems.
• A strong analytical and problem-solving mindset, with the ability to translate complex business problems into tractable quantitative models.
• An aptitude for staying current with the latest research and technical advancements in machine learning and optimisation.

Check out Life at Huawei Ireland Research Centre: https://www.youtube.com/watch?v=3gR64sYSnOA&feature=youtu.be

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