Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Graph Architect

CREGG Recruitment
11 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer - Graph Data Science

Senior Machine Learning Engineer - Graph ML

Agentic AI Data Scientist – Architect the Future

Senior Lead Machine Learning Scientist

Machine Learning Researcher in Bioinformatics (Research Fellow)

Data Scientist

Graph Architect Excellent opportunity for a Graph Architect to join a growing and innovative technology company.

Check you match the skill requirements for this role, as well as associated experience, then apply with your CV below.

The Graph Architect will be responsible for designing, implementing, and optimizing graph databases, with a strong focus on utilizing Neo4j or AWS Neptune graph databases.

Key Responsibilities: Design and implement graph databases to efficiently store networks of entities; with a specific focus on real-time retrieval of information.

Explore the payments domain to identify untapped opportunities and potential risks, and support the inclusion of domain context within graphs.

Play a pivotal role in preparing the analytics infrastructure by developing strategies to optimize queries, graphs, and indexing strategies for graph operations.

Support the Machine Learning initiatives within the organization by providing query optimization to meet the needs of providing graph insights for real-time and near-real-time decision making.

Ensure compliance with relevant data protection regulations, internal governance and controls, and industry standards.

Act as a mentor to junior data scientists, providing guidance, knowledge sharing, and fostering a culture of continuous learning within the data science team.

Apply extensive research background to explore cutting-edge graph techniques and technologies, staying abreast of industry trends and incorporating innovative approaches into our analytics strategy for payments, underwriting, and merchant monitoring.

Key Requirements: Master's or Ph.D.

degree in Computer Science, Statistics, Mathematics, or a related field, with a strong emphasis on data, networks and/or graphs.

Minimum of 5 years of experience in a senior-level data science or related analytical role, with a proven track record of leading and delivering complex graph database research, projects and initiatives.

Understanding of graph data model paradigms (e.g., LPG, RDF) and experience with graph languages (e.g., Gremlin & SparQL)
- hands-on experience is required.

Proven experience in designing and implementing graph databases, knowledge graph with a focus on Neo4j or Neptune for knowledge graph applications.

Solid understanding of graph data design, graph data modeling and graph analytics.

Strong proficiency in optimization of graph databases both from a storage and retrieval perspective.

Experience with other relevant programming languages, such as Python, R, or similar languages.

Knowledge of data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy) and experience in building and deploying machine learning models using frameworks such as TensorFlow, Keras, or Scikit-learn, will be an advantage.

Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).

Excellent communication and interpersonal skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders and senior executives.

For further information please contact Loretta Flynn Skills: data science; python graph architect AI machine learning graph specialist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Best Free Tools & Platforms to Practise AI Skills in 2025/26

Artificial Intelligence (AI) is one of the fastest-growing career fields in the UK and worldwide. Whether you are a student exploring AI for the first time, a graduate looking to build your portfolio, or an experienced professional upskilling for career growth, having access to free tools and platforms to practise AI skills can make a huge difference. In this comprehensive guide, we’ll explore the best free resources available in 2025, covering AI coding platforms, datasets, cloud tools, no-code AI platforms, online communities, and learning hubs. These tools allow you to practise everything from machine learning models and natural language processing (NLP) to computer vision, reinforcement learning, and large language model (LLM) fine-tuning—without needing a huge budget. By the end of this article, you’ll have a clear roadmap of where to start practising your AI skills for free, how to build real-world projects, and which platforms can help you land your next AI job.

Top 10 Skills in Artificial Intelligence According to LinkedIn & Indeed Job Postings

Artificial intelligence is no longer a niche field reserved for research labs or tech giants—it has become a cornerstone of business strategy across the UK. From finance and healthcare to manufacturing and retail, employers are rapidly expanding their AI teams and competing for talent. But here’s the challenge: AI is evolving so quickly that the skills in demand today may look different from those of just a few years ago. Whether you’re a graduate looking to enter the industry, a mid-career professional pivoting into AI, or an experienced engineer wanting to stay ahead, it’s essential to know what employers are actually asking for in their job ads. That’s where platforms like LinkedIn and Indeed provide valuable insight. By analysing thousands of job postings across the UK, they reveal the most frequently requested skills and emerging trends. This article distils those findings into the Top 10 AI skills employers are prioritising in 2025—and shows you how to present them effectively on your CV, in interviews, and in your portfolio.

Translucent Careers: Senior Artificial Intelligence Engineer in London

The global landscape of artificial intelligence is evolving rapidly, and nowhere is this transformation felt more strongly than in the financial and accounting industries. AI is no longer just a supporting technology; it is becoming the backbone of innovation, efficiency, and decision-making. One of the most exciting companies at the forefront of this movement is Translucent, a dynamic business redefining how accounting professionals work with AI-driven tools. For professionals seeking to combine technical excellence with meaningful industry impact, Translucent represents a rare career destination. At the heart of their current expansion is an opening for a Senior Artificial Intelligence Engineer in London. This role combines high-level technical leadership, hands-on development, and an opportunity to influence the direction of an emerging force in AI. In this article, we’ll explore: Who Translucent are and why they matter. The significance of AI in financial technology (fintech) and accounting. A deep dive into the Senior AI Engineer role. Skills and requirements needed for success. Career growth and opportunities at Translucent. How artificialintelligencejobs.co.uk helps professionals connect with transformative employers like Translucent.