Senior Data Scientist (Graph ML)

TL;DR

Senior Data Scientist (Graph ML): Designing and deploying production-grade graph machine learning solutions and Graph Neural Networks (GNNs) with an accent on solving complex real-world problems using large-scale datasets. Focus on driving Graph AI adoption, extracting actionable insights via graph algorithms, and leading a team of data scientists.

Location: Hybrid in Athens, Thessaloniki, Limassol, or Nicosia

Company

hirify.global is a global financial services provider focusing on advanced data science and business intelligence solutions.

What you will do

• Design, develop, and deploy Graph Neural Networks (GNNs) and graph-based machine learning solutions for production.
• Transform complex datasets into graph representations to extract actionable insights using advanced analytics and statistical techniques.
• Drive organization-wide adoption of Graph AI by identifying new use cases and evolving the data science strategy.
• Lead and supervise a team of data scientists working on graph-related tasks.
• Collaborate with Data Engineers, Software Engineers, and Product Managers to translate business challenges into scalable solutions.
• Maintain high standards for data preparation, feature engineering, model evaluation, and code quality.

Requirements

• University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field.
• At least 6 years of experience in data science, machine learning and AI, including production experience with GNNs.
• Proficiency with graph databases (e.g., Neo4j, Neptune) and query languages like Cypher or Gremlin.
• Strong programming skills in Python, including Pandas, NumPy, and modern ML frameworks.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.
• Fluent in English.

Culture & Benefits

• Attractive remuneration package with performance-related rewards.
• Private health insurance and corporate pension fund.
• Intellectually stimulating work environment with focus on innovation.
• Continuous personal development and international training opportunities.

Hiring process

• Introductory chat with Talent Acquisition.
• Technical interview with the future team.
• Role-specific take-home task.
• Final interview.