Graph Data Analyst
2 weeks ago
Nuclear Sector Specialist
At Amber Labs, we believe in fostering an inclusive and equitable workplace for all. We educate all new hires on our Diversity and Inclusion policies and ensure they are aware of their rights and responsibilities to create a safe and inclusive workplace.
We are seeking an experienced Graph Data Scientist to join our End-User Computing (EUC) team within the Nuclear Sector. The successful candidate will play a key role in designing, analyzing, and leveraging graph data models to support complex nuclear operations, research, and safety processes.
- Design and implement graph-based data models for analyzing 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 analyze 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).
About You:
- £70,000 - £100,000 per year salary.
- 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).
- Expertise in applying graph theory, graph algorithms, and network analysis in data science projects.
- Strong background in machine learning, predictive modeling, 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.
- Experience working in nuclear energy, engineering, or other highly regulated industries.
- Familiarity with artificial intelligence (AI) techniques applied to graph data structures, such as knowledge graphs.
- Experience with Natural Language Processing (NLP) and its integration with graph data for semantic analysis.
- Proficiency with data visualization tools such as Power BI, Tableau, or GraphML.
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