Senior Data Scientist – Graph Machine Learning
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
How to Apply
Interested candidates are kindly requested to send their CV to the HR Manager at careers@xm.com.
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About Company
XM
XM is a leading international FinTech company, committed to shaping the future of online trading through innovative solutions. Established in 2009, XM has grown exponentially with a global team of over 1400 employees around the world. Headquartered in Cyprus, XM also operates from offices in Greece, UK, UAE, USA, South Africa, and Uruguay. Guided by its core values, Big. Fair. Human., XM consistently ranks as a top-rated workplace, having received Platinum accreditation from Investors In People, alongside consistent recognition as one of the top Best Workplaces™.
If you're a motivated and passionate professional eager to contribute and grow, we welcome you to explore our current job openings and apply to be part of a team where your potential can truly shine. www.xm.com/careers