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Senior Data Scientist – Graph Machine Learning

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  • hybrid
  • Full-time
  • Data Science and Business Intelligence
  • Athens
  • Limassol
  • Nicosia
  • Thessaloniki
Work arrangement
hybrid
Employment
Full-time
Stated compensation
Not specified
Stated sponsorship
Not stated
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Requirements

2 with evidence7 unclear or unstated
Remote policy
hybrid
“Provider workplace type: hybrid”
From employer posting metadata
Minimum experience (years)
6
“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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Employment type
Full-time
8 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
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Security clearance
Not mentioned
Timezone / hours
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Citizenship requirement
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Compensation
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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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.
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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  All applications will be treated with strict confidentiality! By submitting this application, I confirm that I have read and agree to the terms of the Privacy and Data Protection Notice and the Confidentiality Undertaking.
Original formatting and links

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 

All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy and Data Protection Notice and the Confidentiality Undertaking.

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