Data Scientist | Permanent | Hybrid working in London |
The Role
You will drive the development of machine learning systems that power a global exchange and data platform. You will work at the intersection of NLP, recommendation systems, and time-series forecasting, building production-grade solutions that directly impact trading decisions. This role offers the opportunity to work on semantic search, hybrid recommendation engines, and predictive models.
What You’ll Do
- NLP & Search: Design and deploy models for entity matching, semantic search, and text classification.
- Recommender Systems: Build engines combining collaborative filtering, content-based filtering, and business rule layers.
- Forecasting: Develop time-series models to predict market trends and pricing dynamics.
- Transformer Models: Fine-tune and deploy models such as BERT and sentence transformers for production use.
- ML Pipelines: Implement pipelines on cloud infrastructure using PySpark for large-scale data processing.
- Collaboration: Work with engineers to integrate models via REST APIs and batch processing.
What We’re Looking For
- Experience: 3+ years in data science or ML engineering, taking projects from research to production.
- Education: Bachelor's degree or higher in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Physics; PhD welcome).
- NLP Expertise: Hands-on experience with modern NLP, including transformer models, embeddings, and semantic search (RAG systems highly desirable).
- Foundational ML: Strong foundation in statistical learning, classical ML (random forests, gradient boosting), and model validation.
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