Required skills
- Artificial Intelligence
- Algorithm Design
- Data Analysis
- Business Intelligence Development
- Google BigQuery
- Apache Impala
- Signals Intelligence
- Data Architecture
- Information Engineering
- Data Fusion
- Data Integration
- Data Profiling
- Imagery Intelligence
- Information Architecture
- Intelligence Analysis
- Data Intelligence
- Open Source Intelligence
- Smart Data
- DataOps
- SQL Databases
- Database Engines
- Web Intelligence
- Enterprise Application Integration
- Business Intelligence Development Studio
- Data Science
- Data Assimilation
- Knowledge Representation
- Infoplus
- AWS Data Analytics
- Adaptive Insights
- Azure Data Analytics
- Artificial Intelligence Markup Language (AIML)
Job description
Your Profile Essential skills/knowledge/experience: Retrieval methods, search strategies, and RAG architectures. LLM architectures, reasoning techniques, and agentic systems. Evaluation frameworks, experimentation, and statistical methods. Strong hands-on SQL and data analysis skills using GCP, BigQuery, Teradata, or equivalent technologies. Research methodo
Requirements
Essential skills/knowledge/experience:
Retrieval methods, search strategies, and RAG architectures.
LLM architectures, reasoning techniques, and agentic systems.
Evaluation frameworks, experimentation, and statistical methods.
Strong hands-on SQL and data analysis skills using GCP, BigQuery, Teradata, or equivalent technologies.
Research methodology, literature review, and hypothesis-driven experimentation; comfortable consuming research.
Python programming and AI prototyping skills.
Ability to convert research insights into practical prototypes, experiments, and recommendations.
Strong analytical thinking and structured problem-solving skills.
Ability to collaborate effectively across AI, data, architecture, and product teams.
Clear written and verbal communication skills, with the ability to explain complex technical concepts.
Awareness of responsible AI, model limitations, evaluation risks, and enterprise governance considerations.
Experience working in complex enterprise data environments.
Desirable skills/knowledge/experience: At least some exposure to the following is expected:
Semantic layers and metrics modelling; ontologies and knowledge representation; knowledge graphs and graph-based reasoning concepts.
Taxonomy and metadata design; NL2SQL, Text-to-SQL, broader NL2* methods, conversational analytics and Dialogue with Data (DwD) approaches; LBG data architecture and data product concepts.
Project details
- Start: flexible
- Remote: onsite
- Location: Somerset, United Kingdom, GB
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