Graph Specialist

Position Overview: 

As a Senior Graph Specialist, you will play a critical role in designing, implementing, and 

optimizing highly scalable graph databases, with a primary focus on Neo4j and AWS Neptune. 

You will lead complex analytical projects, mentor data engineers and scientists, and 

collaborate extensively with key stakeholders to deliver cutting-edge financial risk and 

compliance data solutions. This is an opportunity to directly impact our proprietary AI 

platform's ability to combat fraud and ensure regulatory compliance. 

How you will contribute: 

● Graph Databases: Lead the end-to-end design and implementation of highly 

performant graph databases to efficiently model and store complex networks of 

entities, ensuring real-time information retrieval for critical decisions. 

● Innovation in Payments and Risk Products: Explore the payments domain to identify 

untapped opportunities and potential risks, and support the inclusion of domain context 

within graphs. 

● Scalability and Growth: Architect and implement robust strategies for optimizing graph 

queries, data models, and indexing across large-scale datasets, ensuring the 

scalability and high availability of our analytics infrastructure. 

● Machine Learning: 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. 

● Data Governance: Ensure compliance with relevant data protection regulations, 

internal governance and controls, and industry standards. 

● Mentorship: Provide expert mentorship and technical leadership to data engineers and 

scientists, fostering a culture of continuous learning and excellence. 

● Research and Innovation: 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. 

● Ad-hoc Analysis and Problem Solving: Conduct ad-hoc analyses to address specific 

business challenges or inquiries by the senior leadership. Provide quick and insightful 

solutions to support decision-making. 

● Documentation and Knowledge Sharing: Document graphs, methodologies, and 

findings comprehensively, facilitating knowledge transfer within the team and ensuring 

transparency for stakeholders. 

● Cross-functional Collaboration: Collaborate with cross-functional teams, including 

product managers, engineers, and business stakeholders, to translate business 

requirements into graph solutions that drive business value across the organization. 

● Continuous Learning and Development: Stay abreast of emerging technologies, 

methodologies, and industry best practices to continually enhance your skills and bring 

innovative approaches to the team. 

Desired Experience: 

● 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. 

● 5+ years of hands-on, senior-level experience in graph database architecture, 

engineering, or a related analytical role, with a demonstrable track record of leading 

and successfully delivering complex, production-grade graph database projects and 

initiatives. 

Knowledge, Skills & Abilities:  

● Deep expertise and hands-on experience with graph data modelling paradigms (e.g., 

LPG, RDF) and graph query languages (e.g., Gremlin, SparQL, Cypher). 

● Extensive experience in designing and implementing graph databases, knowledge 

graph with a focus on Neo4j or AWS Neptune for knowledge graph applications. 

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

Familiarity with machine learning and GenAI concepts and their application in graph 

analytics (e.g. GNNs) is a significant advantage. 

● Experience with cloud-based database solutions and knowledge of distributed 

database systems. 

● 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. 

● Proven experience with CI/CD tools (e.g., GitHub Actions, Jenkins or equivalent), 

version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, 

Kubeflow, or equivalent). 

● Excellent problem-solving skills and the ability to work in a collaborative team 

environment. 

● Excellent communication and interpersonal skills, with the ability to effectively convey 

complex technical concepts to non-technical stakeholders and senior executives. 

● Proven experience in developing and implementing data-driven strategies and 

roadmaps, with a strong focus on driving business growth and innovation through data 

analytics. 

● Strong problem-solving abilities and a strategic mindset, with the capacity to identify 

opportunities for data-driven innovation and drive positive outcomes for the 

organization.