Graph Data Scientist, Amber Labs

• We are seeking an experienced Graph Data Scientist to join our End-User Computing (EUC) team within the Nuclear Sector
• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field
• Strong experience with graph database technologies (e.g., Neo4j, Amazon Neptune, or similar) and proficiency in graph query languages (e.g., Cypher, Gremlin)
• Expertise in applying graph theory, graph algorithms, and network analysis in data science projects
• Strong background in machine learning, predictive modelling, and data mining, with experience in using graph data to develop advanced analytics
• Proficient in programming languages such as Python, R, Java, or Scala for data manipulation and model development
• Familiarity with cloud platforms (Azure, AWS, GCP) for deploying machine learning models and graph-based analytics
• Knowledge of DevOps practices, including CI/CD for model deployment, versioning, and monitoring in production environments
• Hands-on experience with ETL tools, integrating data into graph databases from diverse sources
• Strong understanding of data security, governance, and compliance standards in highly regulated environments, particularly in the nuclear sector
• Experience in data visualization for graph-based data, using tools like Neo4j Bloom or other visual interfaces
• All employees are required to meet the Baseline Personnel Security Standard

Desirable

• The successful candidate will play a key role in designing, analysing, and leveraging graph data models to support complex nuclear operations, research, and safety processes
• You will work closely with engineers, architects, and data teams to develop graph-based analytics, ensuring insights from complex and interconnected datasets are translated into meaningful actions within the highly regulated nuclear industry
• Design and implement graph-based data models for analysing complex relationships within nuclear engineering, safety, and operations systems using tools like Neo4j, GraphX, and Gremlin
• Conduct exploratory data analysis (EDA) and use graph algorithms (e.g., pathfinding, community detection, centrality) to gain insights from complex datasets
• Develop and deploy machine learning models on graph structures for predictive analytics, anomaly detection, and risk analysis, supporting nuclear operations and safety requirements
• Perform statistical analysis and data mining on large-scale, multi-dimensional datasets to identify key trends and patterns
• Collaborate with nuclear engineers, data scientists, and IT teams to understand data sources and apply graph analytics to enhance system performance, reliability, and safety
• Implement and optimize graph query performance using languages like Cypher and tools like Neo4j to analyse real-time data streams
• Work with cloud-based platforms (AWS, Azure, GCP) and on-premise systems to build, train, and deploy graph-based models in production environments
• Ensure compliance with data governance and security protocols related to the nuclear sector, working within stringent regulatory frameworks to ensure the safety and integrity of data systems
• Collaborate on the development of data pipelines and ETL processes to integrate diverse sources of data into graph databases, ensuring scalability and reliability
• Engage with DevOps teams to automate the deployment of graph-based data solutions and manage model lifecycle processes (ML Ops)
• Produce technical reports, dashboards, and visualizations to present complex graph-based findings to non-technical stakeholders and decision-makers

• Our Talent Acquisition Team will be in touch to advise you on the next steps. We have a two-stage interview process for most of our consultants. In certain cases, we may include a third and final stage, which is a conversation with the company Partners. This will only be considered if deemed necessary