Senior Data Scientist – Graph Machine Learning

The Role:

We are looking for a Senior Data Scientist specializing in Graph AI to join our growing Data Science team. In this role, you will design and deploy production-grade graph machine learning solutions, working with Graph Neural Networks (GNNs), graph databases, and large-scale datasets to solve complex real-world problems.

You will play a key role in shaping the company's Graph AI capabilities, collaborating with cross-functional teams and mentoring other data scientists while delivering innovative, business-impacting solutions.

The main responsibilities of the position include:

• Design, develop, and deploy Graph Neural Networks (GNNs) and graph-based machine learning solutions
• Transform large, complex datasets into graph representations and extract actionable insights using advanced analytics, graph algorithms, and statistical techniques.
• Drive the adoption of Graph AI across the organisation by identifying new use cases and contributing to the evolution of the company's data science strategy.
• Communicate complex technical concepts and model outcomes clearly to both technical and business audiences.
• Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality.
• Leverage technologies such as Python, Graph Neural Networks, graph databases, modern ML frameworks, and cloud-based data platforms to build innovative data solutions
• Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics
• Lead and supervise a team of data scientists working on graph-related tasks
• Partner closely with Data Engineers, Software Engineers, Product Managers, and business stakeholders to translate business challenges into scalable Graph AI solutions.

Main 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 hands-on experience in designing, training and optimising Graph Neural Networks (GNNs) for production applications.
• Experience working with relational and non-relational databases
• Solid experience working with graph databases (e.g., Neo4j, Neptune) and proficiency in graph query languages (e.g., Cypher or Gremlin).
• Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly
• Strong programming skills in Python and experience with Pandas, NumPy, and similar data analysis libraries
• Strong analytical thinking, problem-solving ability, and attention to detail.
• Excellent communication skills and the ability to work collaboratively in a team environment
• Fluent in English

Benefit from:

• Attractive remuneration package plus performance related reward
• Private health insurance
• Corporate pension fund
• Intellectually stimulating work environment
• Continuous personal development and international training opportunities

The Hiring Experience: What Awaits You

• Let’s Connect – Intro Chat with Talent Acquisition
• Deep Dive – First Interview with Your Future Team
• Bring It to Life – Role-Specific Take-Home Task
• Final Connection – Final Interview