Graph Architect

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