Senior Data Scientist - Search

Location: Hamburg or Berlin, Germany

Salary: €70,000–€85,000 yearly

Company

hirify.global is a European e-commerce company combining fashion and technology to deliver personalized online shopping experiences.

What you will do

• Design and develop machine learning algorithms for personalized shopping experiences.
• Deploy models to production and ensure performance, scalability, and operational ownership.
• Improve retrieval and reranking systems with data-driven approaches instead of business-logic-heavy solutions.
• Build and manage data pipelines for large-scale machine learning applications.
• Collaborate with technical and non-technical stakeholders to establish deployment standards and best practices.

Requirements

• Strong proficiency in Python or another scientific computing language.
• Strong SQL skills and experience with analytical or transactional databases.
• Solid understanding of machine learning, statistical evaluation methods, data structures, and algorithms.
• Experience building and deploying machine learning solutions that deliver business value.
• Experience handling large datasets and designing data pipelines.
• Excellent written and verbal English communication skills.

Nice to have

• Experience with BigQuery, GCP Vertex AI, Amazon SageMaker, or other cloud platforms.
• Knowledge of generative AI, agentic frameworks, recommendation, retrieval, or reranking systems.
• Experience with MLOps frameworks such as MLFlow or Kubeflow.
• Knowledge of deep learning, computer vision, time series, graph neural networks, statistical testing, or Gaussian Processes.
• Practical experience with Docker, infrastructure as code, CI/CD, or interactive dashboards.

Culture & Benefits

• Flat hierarchies, direct communication, and pragmatic decision-making.
• Ownership, trust, and clear responsibility in a fast-paced environment.
• Inclusive culture focused on acceptance, inclusion, and diverse perspectives.
• Team lunches, afterwork drinks, company events, and other employee benefits.

Hiring process

• Apply online through the career page.
• The recruiting team will respond as soon as possible.