Principal Data Scientist (AdTech)

TL;DR

Principal Data Scientist (AdTech): Lead design, build, and deployment of large-scale AI recommendation systems and advanced time series forecasting models for vendor success in a global food delivery platform with an accent on multi-objective optimization, causal inference, and real-time decision algorithms. Focus on strategic leadership, mentoring, and driving vendor recommendation data science roadmap and commercial impact.

Location: Hybrid in Berlin, Germany with relocation support to Germany

Company

hirify.global is a leading global local delivery platform operating in over 70 countries, headquartered in Berlin, Germany, listed on the Frankfurt Stock Exchange and part of the MDAX index.

What you will do

• Lead end-to-end design, build, and deployment of AI recommendation systems impacting millions in vendor vertical.
• Own architecture and modeling for Next Best Action framework to optimize vendor success metrics.
• Lead advanced time series modeling for demand prediction and vendor forecasting.
• Provide technical authority on take rate optimization using causal inference and statistical rigor.
• Collaborate cross-functionally with Product, Engineering, and Commercial teams to align on recommendation strategies.
• Mentor and raise the bar for data science excellence across the organization.

Requirements

• Must be located in or willing to relocate to Germany with hybrid work model in Berlin.
• Expertise in large-scale recommendation systems and sequential/time series modeling.
• Strong skills in causal inference, multi-objective optimization, and probabilistic modeling.
• Experience deploying models in production using Python, Keras, and scikit-learn.
• Proven strategic leadership and ability to influence senior stakeholders.
• English proficiency at least B2 level (job posting in English).

Nice to have

• Experience with Reinforcement Learning, Multi-Agent RL, or contextual bandits.
• Knowledge of Game Theory or Mechanism Design for platform optimization.
• Contributions to large-scale recommendation or time-series forecasting research.
• Experience designing feature stores and serving pipelines for sequence/time-series data.

Culture & Benefits

• Hybrid work model with 2 days per week on-site at Berlin campus.
• 27 days holiday plus extra days after 2nd and 3rd year.
• 1,000 € educational budget, language courses, parental support, and Udemy access.
• Health checkups, meditation, gym and bicycle subsidies.
• Employee share purchase plan, sabbatical bank, public transport discounts, insurance, and pension plan.
• Digital meal vouchers, food discounts, and corporate discounts.
• Relocation support to Berlin with dedicated resources and guides.

Hiring process

• Structured interviews including technical and cultural fit assessments.
• Evaluation of data science expertise and problem-solving skills.
• Clear communication of expectations and support throughout the process.