Director, Data Science - Deep Learning & AI

Job Description

We are seeking a Director of Data Science, Deep Learning to lead our deep learning team within the AdTech space, specifically within the Vendor Data team, to shape the future of AI-driven ads and deals at Delivery Hero. In this pivotal role, you will jointly architect state-of-the-art deep learning models, influence AI strategy, and develop cutting-edge methodologies to significantly enhance the success of thousands of vendors - restaurants, shops, and local businesses - across our platform.

As a senior leader within the Vendor Team, you will be instrumental in building and optimising our AdTech products by leveraging advanced deep learning techniques. These AI models will play a pivotal role in our AdTech ecosystem, helping vendors to maximise visibility, enhance their conversion rate, and drive substantial revenue growth.

Operating in nearly 70 countries, our AdTech infrastructure connects millions of businesses with their ideal customers daily. With AdTech projected to generate over €1 billion in revenue in 2024 / 25, your leadership in deep learning-driven data will be critical in shaping our profitability strategy and advancing our market position.

Key Responsibilities :

Deep Learning Mastery : Exceptional expertise in designing and implementing advanced deep learning architectures, particularly transformers and other sequence-based attention-driven AI models, generative ranking approaches, and long-term interest networks for sophisticated user personalisation in AdTech.

Rigorous Model Evaluation and Business Impact : Proficient in establishing comprehensive evaluation frameworks for deep learning models, encompassing both internal model-centric metrics (such as NCE, ROCAUC, PRAUC) and the meticulous measurement of business metrics during live A / B testing and experimentation.

Cross-Functional Leadership and Alignment : Demonstrated ability to collaborate and align effectively across diverse functions, including engineering, commercial, and product teams, to drive shared goals and ensure the successful, impactful success of deep learning initiatives.

Scalable MLOps and Data Engineering : Proven leadership in developing and maintaining highly scalable and robust data and feature pipelines, ensuring the efficient training, deployment, monitoring, and ongoing performance of deep learning models in high-throughput production environments.

Technical Vision and Continuous Innovation : Knowledge at the forefront of deep learning and machine learning engineering (MLE) trends and approaches, actively driving the team to adopt cutting-edge methodologies. Possesses the expertise to collaborate with senior team members in defining the technical roadmap and leveraging advanced data processing tools like MonteCarlo and dbt to achieve ambitious team objectives.

Qualifications

Extensive Leadership Experience : At least eight years of professional experience leading and scaling high-performing data science and deep learning teams, with a proven track record of applying advanced AI modelling methods in domains such as AdTech, digital marketplaces, or computational economics.

Advanced Academic Background : A master's degree or higher in a quantitative field such as mathematics, physics, computer science, or a related discipline.

Deep Technical Proficiency : Strong technical foundation as a previous individual contributor, expert in Python and SQL, with hands-on mastery of deep learning frameworks including Keras, TensorFlow or PyTorch, alongside data manipulation libraries such as Pandas, PySpark, and NumPy.

Cloud-Scale Data Expertise : Demonstrated expertise in managing, modelling, and deploying deep learning solutions with high-volume, real-time data within cloud environments.

Strategic Communication : Exceptional ability to communicate complex deep learning concepts and their business implications clearly and concisely to both technical teams and senior leadership.