Senior 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. 

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