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
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