As a Senior Data Scientist, you will drive innovation in data processing methods, support product development, and collaborate with teams to enhance methodologies and standards.
Senior Data Scientist – Graph Machine Learning
📅 Jul 28
Graph Neural NetworksGraph DatabasesPythonData Visualization
📜 Description
- 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
🛠️ 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
- Let’s Connect – Intro Chat with Talent Acquisition
✨ Benefits
- Attractive remuneration package plus performance related reward
- Private health insurance
- Corporate pension fund
- Intellectually stimulating work environment
- Continuous personal development and international training opportunities
Full job description
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
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