Senior Data Scientist – Deep Learning & Recommendation Systems
Hamburg, Germany (Hybrid) | Full-Time
Are you interested in solving complex machine learning problems at scale?
We are supporting an innovative technology company in Hamburg looking for a Senior Data Scientist to join a highly technical team developing large-scale deep learning solutions for recommendation, ranking and personalisation.
You will work on production machine learning systems where advanced models directly influence user experiences and business outcomes, developing intelligent algorithms that understand behaviour, optimise relevance and deliver personalised experiences at scale.
Tasks
- Build and optimise deep learning models for recommendation, ranking and personalisation
- Develop scalable machine learning solutions using modern deep learning techniques
- Work with large-scale datasets to improve model performance and user relevance
- Design experiments, evaluate model performance and validate new approaches
- Take ownership of ML models from research and development through to production deployment
- Collaborate closely with engineers and product teams to deliver measurable business impact
- Contribute technical expertise and best practices within the machine learning community
Requirements
- 7+ years of experience in Data Science, Machine Learning or Applied Science
- Extensive experience building production machine learning systems
- Strong hands-on experience with deep learning frameworks such as PyTorch and/or TensorFlow
- Experience developing recommendation systems (RecSys), ranking algorithms or personalisation models
- Strong Python and SQL skills
- Experience working with large-scale production datasets
- Strong understanding of experimentation, model evaluation and production ML workflows
Benefits
- Competitive salary package up to €140,000, depending on experience
- Hybrid working model in Hamburg
- International English-speaking environment
- Opportunity to work on technically challenging deep learning and recommendation systems
- Flexible working arrangements
- Relocation support available
- Strong opportunities for technical ownership and career growth
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