Senior Data Scientist (Graph & Neo4j)

About us:

Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂

Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfill their dreams and objectives.

Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.

The Role:

We are looking for a Senior Data Scientist for one of our clients. You will lead the design and implementation of graph-based models to solve high-impact problems—ranging from fraud detection and recommendation engines to complex GraphRAG architectures. As a Neo4j specialist, you will turn interconnected data into a strategic competitive advantage for our clients. You are a perfect candidate if you are growth-oriented, you love what you do, and you enjoy working on new ideas to develop exciting products and growth features.

What we are looking for:

• 3+ years of hands-on experience specifically with Neo4j and its GDS library.
• Expert proficiency in Python
• Deep understanding of graph theory, network science, and linear algebra.
• Experience with ETL/ELT pipelines to move data from relational databases or data lakes into Neo4j.
• Proven track record of deploying ML models into production environments (Docker, Kubernetes, or Cloud-native ML platforms).
• Beyond Cypher, a solid grasp of SQL is essential for data preparation.
• Time zone: CET (+/- 3 hours). We are unable to consider applications from candidates in other time zones.

Responsibilities:

• Design and architect scalable graph schemas in Neo4j that represent complex real-world entities and their relationships.
• Use the Neo4j Graph Data Science (GDS) library to implement centrality, community detection, similarity, and pathfinding algorithms.
• Build and productionize machine learning models that leverage graph features (node embeddings, Graph Neural Networks) to improve accuracy over traditional ML approaches.
• Write and optimize complex Cypher queries to extract insights and power real-time applications.
• Collaborate with AI engineers to integrate Knowledge Graphs into LLM workflows, improving the factuality and context-awareness of generative AI solutions.
• Use tools like Neo4j Bloom or Linkurious to translate complex graph insights into actionable stories for stakeholders.

What we offer:

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Enjoy a harmonious work-life balance with consistent 8-hour working days with clients.

Flex days, so you can recharge

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Compensation

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