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Senior Graph Data Scientist

1 month ago


London, Greater London, United Kingdom Amber Labs Full time

Job Title: Senior Graph Data Scientist

Job Summary:

We are seeking an experienced Senior Graph Data Scientist to join our End-User Computing (EUC) team within the Nuclear Sector at Amber Labs. 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.

Key Responsibilities:

  • 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.

Requirements:

  • 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.

What We Offer:

  • A rapidly expanding start-up where personal growth is a part of our DNA.
  • A flexible work environment focused on deliverable outcomes.
  • Private medical insurance through Aviva.
  • A company pension plan through Nest.
  • 25 days of annual leave plus UK bank holidays.
  • Access to Perkbox, a global employee rewards platform offering discounts, perks, and wellness resources.
  • A generous employee referral program.
  • A highly collaborative and collegial environment with opportunities for career advancement.
  • The freedom to choose your preferred device, PC or Mac.