Senior Data Scientist – Graph Machine Learning

Posted 3 Days Ago
Be an Early Applicant
4 Locations
Remote or Hybrid
Senior level
Fintech • Financial Services
The Role
Design, develop, and deploy production Graph Neural Network solutions. Transform large datasets into graphs, apply graph algorithms and analytics, ensure data and model quality, lead a team of data scientists, and collaborate with engineers and stakeholders to deliver scalable Graph AI solutions.
Summary Generated by Built In
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!

Skills Required

  • University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or related quantitative field
  • At least 6 years of experience in data science, machine learning, and AI, including hands-on experience designing, training, and optimizing Graph Neural Networks for production
  • Experience designing, training, and optimizing Graph Neural Networks (GNNs) for production applications
  • Experience working with relational and non-relational databases
  • Solid experience with graph databases (e.g., Neo4j, Amazon Neptune) and proficiency in graph query languages (Cypher or Gremlin)
  • Strong programming skills in Python and experience with Pandas and NumPy
  • Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly
  • Proven experience leading or mentoring data scientists and collaborating cross-functionally
  • Excellent communication skills and fluency in English
  • Strong analytical thinking, problem-solving ability, and attention to detail
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The Company
3,353 Employees
Year Founded: 2009

What We Do

XM is a trading platform trusted by over 20 million traders, offering easy access to 1400+ global assets with low spreads, exceptional conditions, and super-fast execution for Forex and CFD trading.

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