Senior Data Scientist – Graph Machine Learning

The Role: 

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

XM publishes this vacancy on its own careers site. Applications go straight to XM: use the Apply button on this page.