Senior Data Scientist – Graph Machine Learning
XMThe 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