Data Scientist (Quick Commerce)

TL;DR

Data Scientist (Quick Commerce): Develop and deploy AI/ML models to automate product catalog enrichment and assortment curation with an accent on NLP, classification, and recommendation systems. Focus on designing scalable, reliable ML solutions and driving measurable business impact through experimentation and model validation.

Location: Hybrid in Berlin, Germany with relocation support

Company

hirify.global is a leading global local delivery platform operating in over 70 countries, headquartered in Berlin, Germany, focused on pioneering quick commerce and powered by advanced technology.

What you will do

• Design, experiment, and deploy AI/ML models to automate product attribute enrichment and moderation at scale.
• Drive experimentation by formulating hypotheses, validating model performance, and analyzing business impact.
• Develop ML models for product categorization, attribute extraction, and assortment curation.
• Apply state-of-the-art models including NLP, deep learning, LLMs, and AI agents.
• Collaborate closely with machine learning engineers and software engineers to ensure scalable and reliable production solutions.
• Contribute to the long-term vision of AI-driven catalog automation while delivering short-term business wins.

Requirements

• Location: Hybrid work model with presence in Berlin, Germany
• 3+ years of experience applying data science and machine learning in production, especially in consumer-facing applications.
• Expertise in NLP, classification, recommendation systems, and LLMs or agentic AI frameworks.
• Strong statistical skills and experience with large-scale experimentation and model validation.
• Proficient in Python and deploying ML models with best practices for observability and performance.
• Ability to work cross-functionally with engineers and product stakeholders.

Nice to have

• PhD in AI, Machine Learning, or related field.
• Experience scaling catalog automation or content generation systems across markets.
• Experience designing or building agentic AI systems and fine-tuning large language models.
• Familiarity with cloud platforms, preferably GCP.
• Contributions to the data science community such as talks, papers, or open source.

Culture & Benefits

• Hybrid working model with 2 days per week on 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 vouchers, and corporate discounts.
• Relocation support to Berlin with dedicated resources and guides.

Hiring process

• Structured interview process with technical and cultural fit evaluations.
• Preparation resources provided including common interview questions and answers.