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Senior Data Scientist – Graph Machine Learning
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:
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Design, develop, and deploy Graph Neural Networks (GNNs) and graph-based machine learning solutions
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Transform large, complex datasets into graph representations and extract actionable insights using advanced analytics, graph algorithms, and statistical techniques.
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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.
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Communicate complex technical concepts and model outcomes clearly to both technical and business audiences.
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Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality.
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Leverage technologies such as Python, Graph Neural Networks, graph databases, modern ML frameworks, and cloud-based data platforms to build innovative data solutions
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Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics
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Lead and supervise a team of data scientists working on graph-related tasks
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Partner closely with Data Engineers, Software Engineers, Product Managers, and business stakeholders to translate business challenges into scalable Graph AI solutions.
Main requirements:
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University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field
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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.
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Experience working with relational and non-relational databases
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Solid experience working with graph databases (e.g., Neo4j, Neptune) and proficiency in graph query languages (e.g., Cypher or Gremlin).
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Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly
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Strong programming skills in Python and experience with Pandas, NumPy, and similar data analysis libraries
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Strong analytical thinking, problem-solving ability, and attention to detail.
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Excellent communication skills and the ability to work collaboratively in a team environment
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Fluent in English
Benefit from:
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Attractive remuneration package plus performance related reward
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Private health insurance
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Corporate pension fund
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Intellectually stimulating work environment
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Continuous personal development and international training opportunities
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