Job Description
We are seeking a Director, Data Science, AdTech Statistical analysis to lead statistical analysis and analytics in the Vendor Data team shaping the future of data-driven decision-making at Delivery Hero. In this role, you will drive analytical excellence, influence strategy, and develop cutting-edge methodologies to 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 explaining and optimising our Ad Tech products as well as leveraging advanced analytics to improve sales operations & the vendor platform. Your insights will directly impact our AdTech ecosystem, helping vendors maximise visibility, enhancing conversion rates and driving 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 data and statistical analysis will be critical in shaping our profitability strategy and advancing our market position.
1. Define and implement the analytical vision for vendor data, ensuring insights drive measurable business impact.
2. Oversee the development of cutting-edge statistical models to optimise ad placements, vendor pricing strategies, and vendor engagement.
3. Manage the development of robust A/B and multi-armed bandit testing frameworks, leveraging methodologies such as propensity score matching, synthetic control, monte carlo simulation, and structural modeling to determine business impact ensuring statistical robustness.
4. Foster an environment of investigation, fairness and evidence-driven decision making within the vendor data organisation.
5. Drive high-profile initiatives with product, commercial, and engineering teams delivering a global impact.
Qualifications
6. 8+ years professional experience leading high-performing analysis teams applying statistical methods in domains such as ad tech, economics, or digital marketplaces with a pragmatic approach.
7. A master’s degree in mathematics, physics or similar ideally with a focus on probability and statistics.
8. Technical competency from a history as an individual contributor working in Python and SQL using Pandas, NumPy, and statistical libraries (eg statsmodels, Scipy)
9. Expertise in managing and modelling high-volume data in the cloud.
10. Clear and concise communication with experience discussing complex statistical topics with leadership.