We are looking for a curious and technically versatile Data Scientist to join a high-impact AI initiative at the intersection of behavioural analytics, generative AI, and personalisation. You will work on extracting meaningful patterns from complex, multimodal, unstructured data sources and translating them into intelligent, context-aware AI systems. This persona modelling project combines rigorous data science with the latest advances in large language models and retrieval-augmented generation.
This is a hands-on, research-oriented role with real influence over architecture and methodology, ideal for someone who thrives in ambiguous, greenfield environments.
Key Responsibilities:
- Design pipelines to extract communication styles, reasoning patterns, decision-making frameworks, and domain expertise from unstructured text sources (documents, transcripts, reports, communications)
- Apply statistical techniques to identify, validate, and quantify patterns in complex datasets, ensuring findings are robust and reproducible
- Work closely with LLMs to design, test, and refine prompts and model behaviours; translate analytical insights into inputs that meaningfully improve AI system outputs
- Develop, iterate, and systematically evaluate prompts for large language models; build prompt frameworks that ensure consistent, high-fidelity AI responses aligned with specific personas or knowledge domains
- Contribute to the design and optimisation of retrieval-augmented generation architectures, including hybrid and graph-based approaches, to ground AI outputs in structured knowledge
- Build reliable, auditable pipelines for ingesting, cleaning, and processing large volumes of unstructured and semi-structured data; apply best practices for data governance and sensitivity handling
- Define evaluation metrics for AI output quality and personalisation fidelity; design and run experiments to continuously improve model and system performance
- Insight Communication: Present complex analytical findings and AI behaviours clearly to both technical teams and non-technical stakeholders, translating nuance into actionable conclusions
- Collaborate with MR engineers, product teams, and researchers to translate behavioural insights into deployable AI systems.
Skills:
- Strong proficiency in Python (pandas, NumPy, scikit-learn, and NLP libraries such as spaCy, Hugging Face Transformers, LangChain, or similar)
- Solid grounding in statistics: hypothesis testing, distributions, regression, clustering, and model evaluation
- Hands-on experience with Generative AI and LLMs: including prompt engineering, fine-tuning, and output evaluation
- Experience processing and analysing unstructured text data
- Familiarity with multimodal AI systems or analysis across different media formats is a plus
- Familiarity with vector databases and embedding-based retrieval (e.g. Pinecone, Weaviate, FAISS)
- Working knowledge of graph databases or knowledge graph construction is a plus
- SQL proficiency and comfort with data pipeline fundamentals
- Strong experimental and analytical mindset: rigorous about evidence, comfortable with uncertainty
Qualifications:
- Degree in Data Science, Statistics, Computer Science, Computational Linguistics, Cognitive Science, or a related quantitative field
- 4+ years of experience in data science or a closely related discipline
- Demonstrable experience working with LLMs or Generative AI systems in a professional or research context
- Experience in NLP, behavioural analytics, or personalisation systems is a strong advantage
- Familiarity with MLOps practices and deploying models or AI components into production environments is a plus
Location:
- This role can be based in Spain, Serbia, or Dubai.
Some of the benefits you’ll enjoy working with us:
- The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
- The opportunity to form part of an amazing, multicultural community of tech experts.
- A highly competitive compensation package.
Come and join our #ParserCommunity.
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