About the job
We are looking for a graph data engineer. In this role, you will get to work alongside various experts in product and engineering.
Example Responsibilities:
- Develop real-time graph data pipelines that capture and process relevant data, integrating vector databases for efficient similarity searches to uncover patterns indicative of fraudulent activities.
- Deploy the integrated solution to production, ensuring a robust and scalable infrastructure. Conduct benchmarking and performance optimization for both vector and graph databases to meet the demands of real-time fraud detection.
- Design and implement a cohesive system where vector and graph infrastructure complement each other seamlessly, combining their strengths to enhance fraud detection capabilities.
- Collaborate with cross-functional teams to identify specific use cases where vector and graph databases can work in tandem, devising data models that optimize the strengths of both technologies for effective fraud detection.
- Collaborate with the operations team to define and implement efficient maintenance and update strategies for both vector and graph databases, ensuring seamless operation in a dynamic production environment.
- Skills and Experience:
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.
- Extensive experience in designing, implementing, and optimizing real-time graph data pipelines for fraud detection, with a proven track record of deploying solutions to production environments.
- Strong proficiency in graph theory, graph algorithms, and graph databases (e.g., Neo4j, Amazon Neptune, TigerGraph, ...), coupled with extensive knowledge of vector databases (OpenSearch, Milvus, ...).
- Proficient in Python, Java, or Scala for developing and maintaining data engineering pipelines, with expertise in Apache Spark, Flink, and containerization (Docker, Kubernetes). Experienced in cloud platforms (AWS, Azure, Google Cloud) and skilled in working with various databases and data warehouses for efficient data processing and storage.
- Familiar with operations tools such as Terraform, Jenkins, and CloudFormation for automating infrastructure provisioning, deployment, and maintenance in production environments.
- Great to have Experience and Qualifications:
- Solid understanding of embedding techniques, graph neural networks, and their applications in solving real-world problems.
- PhD in Computer Science or a related field with a focus on graph-based machine learning.
- Experience working with large-scale graph datasets and optimizing performance for computational efficiency.
- Contributions to relevant open-source projects.
- Strong analytical and problem-solving skills with a keen eye for detail in optimizing algorithms for performance and scalability.
- Key Characteristics and Attitudes:
In a recent global survey these attributes were valued by Jumios in all locations and functions - we firmly believe in hiring for attitude as well as skill.
- Friendly and supportive
- Adaptable and flexible
- Articulate and persuasive
- High IQ and EQ
- Curious and coachable
- Commercially Aware
- Resilient and tenacious
- Big picture and the detail
- Jumio Values:
IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation
Equal Opportunities:
Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.
About Jumio:
Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders.
Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we're expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others. -
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