Job Description
We are on the lookout for Staff Data Scientists to join the AdTech data science team (Bidding Team) on our journey to always deliver amazing experiences.
As part of our Vendor Team, you’ll be the driving force behind the success of thousands of restaurants, shops, and local businesses. Your contributions will empower vendors with advanced tools to manage their operations, boosting their visibility, and reach. Every feature you help build will create growth opportunities for businesses of all sizes, strengthening Delivery Hero’s ecosystem and impact.
At Delivery Hero, AdTech introduces people to new food they love and enables our partners to meet their future customers at the perfect moment. We have developed a range of products to offer advertising solutions for restaurants helping them to increase their visibility and reach, improve their order conversion, and eventually drive more sales by covering the entire marketing funnel. Operating across over 50 countries around the clock, our Ad Tech connects the ideal advertiser with the ideal customer millions of times every day. Ad Tech is a fundamental area for us on our path to profitability. our data science team is at the heart of this growth, powering personalisation, Ranking, relevance, and recommendation.
You will be a thought leader, driving innovation by designing and deploying our models to the forefront of technology to solve complex problems, delivering revenue for Delivery Hero at the frontline of our growth & profitability journey. In this role you will
1. Drive transformative innovation in AI-powered bidding systems for digital advertising.
2. Lead the creation of state-of-the-art models and strategies that redefine auction dynamics, maximise advertiser ROI, and deliver exceptional user experiences.
3. As an expert, you will elevate our advertising intelligence capabilities, setting new industry benchmarks while shaping the future of data-driven decision-making at scale.
Qualifications
The ideal candidate will demonstrate:
4. Expert AI and ML Expertise:
Mastery of bidding algorithms (eg automated bidding, constrained optimisation, real-time bidding strategies) and cutting-edge approaches to budget pacing and demand forecasting.
Experience with Reinforcement Learning (RL), optimal control, and time-series modeling as applied to strategic market interaction and bid optimisation.
Advanced knowledge of AI frameworks (eg TensorFlow, PyTorch) and their application to ultra-low-latency decision systems for real-time bidding.
5. Advertising Domain Mastery:
Proven experience designing and deploying systems to optimise CPC, CPA, and ROAS metrics for advertisers at scale via bidding and pacing controls.
In-depth understanding of ad auctions, ad markets, and the economic dynamics of programmatic and exchange platforms.
6. Exceptional Data and Statistical Expertise:
Advanced proficiency in Python, SQL, and working with large-scale data from front-end tracking data and bid-request logs.
Ability to solve multi-objective optimisation problems for bidding, balancing metrics such as spend, conversion, and yield.
7. Proven Leadership in AI Systems:
A track record of designing and deploying large-scale AI systems in production, with measurable business outcomes and technical stability and observability.
Experience influencing organisational strategy through actionable, data-driven insights related to market efficiency and auction mechanics.
A history of mentoring others to achieve exceptional technical outcomes while driving alignment across engineering, product, and data organizations.
Nice-to-Haves:
8. Econometrics and Game Theory: Familiarity with econometric models or game theory concepts as applied to auction design, pricing strategies, and market participant incentives in digital advertising.
9. Advanced Reinforcement Learning: Expertise in advanced topics within Reinforcement Learning (RL), such as multi-agent systems, offline RL, or specific optimal control techniques used for high-frequency, complex bid strategies.
10. Production MLOps for Decision Services: Advanced expertise in deploying and monitoring ultra-low-latency decision models (not just prediction models) in a cloud environment (eg GCP/AWS), with a focus on high-volume, real-time serving infrastructure.
11. Deep Time-Series Forecasting: Proven skill in advanced time-series modeling and deep learning (eg LSTMs, attention-based models) for highly accurate and granular budget pacing and demand forecasting in volatile ad markets.