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DEDelivery Hero

Principal Data Scientist - Vendor Recommendations & AI(m/w/x)

Berlin
Full-timeWith Home Office
AI/ML
Data Science

Architecting large-scale AI recommendation systems and Next Best Action (NBA) framework for a delivery platform in 70+ countries. Expertise in large-scale recommendation systems (two-tower, GNNs) for B2B/marketplace required. €1,000 educational budget, plus additional holiday days.

Requirements

  • Expertise in designing/deploying large-scale recommendation systems (two-tower, deep sequence, GNNs) for B2B/marketplace
  • Thought leadership: timeseries analysis, sequence modeling (LSTMs, transformers, forecasting)
  • Proven ability to apply causal inference and advanced experimentation frameworks
  • Deep expertise: analytical frameworks for optimizing commercial metrics (take rate, LTV, churn)
  • Mastery: multi-objective optimization for balancing conflicting vendor KPIs
  • Deep experience: designing/deploying real-time 'Next Best Action' algorithms
  • Strong foundation in Bayesian methods and uncertainty quantification
  • Deep operational knowledge: deploying models using Python (Keras, scikit-learn)
  • Proven ability to define 2+ year technical roadmap for Vendor Recommendation Data Science
  • Ability to influence strategic direction of Product, Engineering, and Commercial leadership
  • Track record: translating complex ML/statistical findings into executive narratives
  • History of mentoring Staff and Senior Data Scientists
  • Ability to raise scientific rigour and production ML excellence
  • Expertise: Reinforcement Learning (RL), Multi-Agent RL, or contextual bandits (advantageous)
  • Familiarity: Game Theory or Mechanism Design for multi-sided platform optimization (advantageous)
  • Major contributions (papers, talks, libraries) in Large-Scale Recommendation Systems or Time-Series Forecasting (advantageous)
  • Expertise: designing feature stores and serving pipelines (advantageous)

Tasks

  • Lead end-to-end development of large-scale AI recommendation systems.
  • Architect the Next Best Action (NBA) framework.
  • Develop models for optimal action sequencing and timing.
  • Lead advanced time series modeling initiatives.
  • Predict demand using time series models.
  • Forecast vendor performance.
  • Analyze long-term vendor base trends.
  • Guide take rate optimization as technical authority.
  • Apply statistical rigor to take rate optimization.
  • Utilize causal methods for take rate analysis.
  • Measure incrementality of vendor pricing levers.
  • Measure efficiency of vendor adtech levers.
  • Partner with Product, Engineering, and Commercial teams.
  • Validate or debunk business hypotheses.
  • Drive alignment on the recommendations strategy.

Education

  • Master's degree

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • two-tower models
  • deep sequence models
  • Graph Neural Networks
  • LSTMs
  • transformers
  • Python
  • Keras
  • scikit-learn
  • Multi-Agent RL
  • contextual bandits
  • feature stores
  • serving pipelines

Benefits

More Vacation Days

  • 27 days holiday
  • Extra holiday day (2nd year)
  • Extra holiday day (3rd year)

Additional Allowances

  • Educational budget (€1,000)
  • Bicycle subsidy
  • Digital meal vouchers
  • Food vouchers

Learning & Development

  • Language courses
  • Udemy Business access

Family Support

  • Parental support

Healthcare & Fitness

  • Health checkups
  • Gym subsidy

Mental Health Support

  • Meditation

Competitive Pay

  • Employee share purchase plan

Workation & Sabbatical

  • Sabbatical bank

Public Transport Subsidies

  • Public transportation discount

Other Benefits

  • Life and accident insurance

Retirement Plans

  • Corporate pension plan

Corporate Discounts

  • Corporate discounts
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