Execute end-to-end data science projects with guidance from senior team members, from problem definition to deployment.
Build and optimise machine learning and NLP solutions that drive client decision-making.
Design scalable data pipelines and workflows using structured and unstructured data.
Apply LLM APIs to build and enhance analytical and client-facing deliverables, including prompt design, RAG architectures, and vector search.
Source, extract, and normalise data from external APIs (REST and GraphQL), handling authentication, pagination, and schema variability; integrate cloud services and modern data platforms into analytical workflows.
Create reusable tools and frameworks that scale insights across clients and projects.
Review, iterate on, and maintain existing code and analytical outputs to ensure accuracy, reliability, and long-term maintainability.
Partner with senior data scientists, engineers, strategists, and client teams to deliver measurable impact.

Extensive experience in Data Science, Machine Learning, applying AI, NLP or related fields.
BSc and/or advanced degree in Statistics, Physics, Economics, Mathematics, Computer Science, or a related field
Strong Python and SQL skills; comfortable working with relational database structures including querying, designing schemas, and building data models; experience with data visualization tools (eg PowerBI, Tableau)
Experience building and deploying ML/NLP solutions in production environments.
Hands-on experience with LLMs and GenAI platforms (e.g. OpenAI, Anthropic, Azure OpenAI).
Familiarity with RAG, vector databases, prompt engineering, and AI application development.
Experience working with cloud platforms (AWS, Azure, or GCP).
Strong statistical and analytical foundations.
Strong cross-functional communication skills; able to work across diverse teams, translate between technical and non-technical stakeholders.

Nucleus

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