ML Data Scientist (Probabilistic Graphical Models)

AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces. We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.

Our Contingent Workforce Solutions (CWS) is one of our service offerings. Acting as an extension of their recruitment teams, we connect them with skilled interim and temporary professionals, fostering workplaces where everyone can contribute and succeed.

Our client, a major UK retail bank, provides every day banking services to over 17 million retail customers. The banks expertise and services span across Business Services, Corporate banking, Wealth Management, Group Functions, Retail and Investment Banking.

On behalf of this organisation, AMS are looking for a Graph, ML Data Scientist for a contract due to run until December 2026 based in either the London or Edinburgh office on a hybrid working model.

Purpose of the role:

The Graph, ML Data Scientist will specialise in leveraging graphical models (such as Bayesian networks and Markov models) and probabilistic reasoning techniques to uncover insights from complex data sets using advanced data analysis and predictive modelling.

What you'll do:

• Design, develop and deploy advanced graph analytics models and algorithms to uncover patterns, anomalies and relationships within large-scale graph datasets.
• Collaborate with cross-functional teams including product, engineering, and business stakeholders to understand data requirements and deliver impactful solutions.
• Implement and optimise graph databases and graph processing frameworks (eg, Neo4j).
• Develop predictive models using machine learning techniques tailored for graph-structured data (eg, node classification, link prediction, community detection).
• Perform data pre-processing, feature engineering, and exploratory data analysis on structured and unstructured datasets.
• Communicate complex data insights clearly and effectively to technical and non-technical audiences.
• Mentor junior data scientists and contribute to best practices in data science and graph analytics within the organisation.
• Demonstrate up to date knowledge on latest research and advancements in graph analytics, network science and related fields.

The skills you'll need:

• Demonstrable professional experience in data science, with a strong focus on graph analytics.
• Proficiency in graph analytics tools and libraries such as Neo4j, NetworkX, GraphX, or similar.
• Strong programming skills in Python & PySpark, with experience in relevant machine learning libraries (eg, scikit-learn, TensorFlow, PyTorch).
• Expertise in graph algorithms including shortest path, centrality, community detection, and graph embeddings.
• Experience with big data technologies and cloud platforms - AWS experience mandatory.
• Excellent problem-solving skills and ability to work independently and collaboratively with strong communication and presentation skills.

Next steps:

This client will only accept workers operating via an Umbrella or PAYE engagement model.

If you are interested in applying for this position and meet the criteria outlined above, please click the link to apply and we will contact you with an update in due course.

AMS, a Recruitment Process Outsourcing Company, may in the delivery of some of its services be deemed to operate as an Employment Agency or an Employment Business