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.

#LI-VH2