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Data Science Leader

vor 2 Monaten


Berlin, Berlin, Deutschland Delivery Hero Vollzeit
Job Overview

We are seeking an experienced Data Science Leader to drive the development of data science components in our Customer Data Platform.

As a key member of the Consumer Insights & Marketing Technology (CIMT) Tribe at Delivery Hero, you will leverage data and advanced analytics to drive customer acquisition and retention in food and grocery deliveries.

Our mission is to optimize and enhance the customer journey through innovative data solutions, including marketing science, customer science, and Generative AI.

As a Data Science Leader, you will work on a diverse range of products, collaborating closely with other data scientists, engaging in senior leadership discussions, and driving technical excellence.

Your role will focus on boosting productivity, improving the machine learning product lifecycle, and leading data science initiatives to foster both individual and team growth within the tribe.

Key Responsibilities
  • Customer Identity Resolution: Develop ML capabilities to identify and deduplicate customers across multiple accounts, using advanced algorithms to provide a unified customer identity view.
  • Behavioral ML Models: Create cutting-edge behavioral ML models for customer-related use cases across Delivery Hero brands, such as predicting future purchases.
  • Marketing Science: Optimize and measure the budget and effectiveness of marketing campaigns and investments.
  • Generative AI: Use generative AI to create and enhance images and descriptions for food and grocery items, improving product listing quality and appeal.
  • Lead Data Science Function: Own the Data Science function for the Customer domain, building a multi-tiered organization that produces high-quality output, fosters personal growth and learning, and offers clear career paths for all Data Scientists.
Requirements
  • 7+ years in data science with a proven track record of building and deploying ML models at scale in production environments.
  • Full Lifecycle Expertise: Proficiency in all stages of the data science product lifecycle, from ideation and development to deployment, scaling, and maintenance.
  • Technical Proficiency: Experience in data engineering, including data ingestion, processing, and management.
  • Production-Scale Solutions: Proven ability to build robust, scalable, and maintainable end-to-end solutions.
  • Collaborative Decision-Making: Strong skills in decision-making and the ability to align and discuss technical solutions with stakeholders and senior leadership.
  • Mentorship: Ability to mentor and guide junior data scientists, fostering a culture of learning and growth within the team.
Nice to Have
  • Marketing Science: Experience in optimizing and measuring marketing campaigns and investments.
  • Knowledge of Generative AI techniques and their application in content creation and enhancement, particularly in the context of e-commerce or digital marketplaces.