Senior Research Data Scientist
Seniority
Senior
Domain
Retail, Customer Data Science, AI Strategy
Responsibilities
Drive design, experimentation, and evaluation of transformer-based models on retail challenges; Explore innovative architectures (sequence-to-sequence, causal transformers, hybrid retrieval + transformer); Develop research-grade prototypes and collaborate with engineers for productionisation; Conduct forward-looking research on generative AI, multimodal learning, and representation learning; Identify emerging AI/ML techniques for retail and consumer analytics; Drive internal thought leadership and define standards; Work with academic groups and research partners; Mentor other data scientists; Partner with internal teams on tooling and platform strategy; Document best practices and reusable assets.
Required skills
Expertise in transformer architectures (BERT, GPT, T5, Time-Series Transformers); Strong hands-on experience with modern deep learning frameworks (PyTorch preferred); Solid grounding in machine learning fundamentals and statistical modelling; Familiarity with distributed training and GPU acceleration; Ability to shape ambiguous research ideas into structured investigations; Curiosity and a learning mindset; Strong data manipulation and engineering skills (PySpark, SQL, cloud-based data tooling); Strong communication skills; Collaborative approach; Passion for turning modelling ideas into business impact.
Preferred skills
Experience in retail, CPG, recommendations, or customer behaviour modelling; Engagement with academic research (publications, workshops, industry collaborations); Familiarity with vector databases, embeddings, and retrieval techniques; Experience working on large datasets (efficient loading, batching, streaming) using PySpark.
