Data Scientist

Synergetic

City of London, United Kingdom

Last month

Applications closed

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Posted: 19 Mar 2026 (Last month)

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Full Stack Data Scientist - AI & Knowledge Systems

About the Role

We are seeking an exceptional Full Stack Data Scientist to join our clients innovation team. This role combines traditional data science expertise with software engineering capabilities to build end-to-end AI solutions. The ideal candidate will have a strong foundation in both developing sophisticated machine learning models and implementing them within production systems. You will work closely with cross-functional teams to transform concepts into scalable AI-powered products.

We are looking for candidates that can combine technical expertise with a true consulting approach.

Responsibilities

Design, develop, and implement advanced machine learning models and AI capabilities
Build and maintain knowledge graphs and causal inference systems
Create probabilistic models to address complex business problems
Scale AI solutions from proof-of-concept to MVP and full production
Collaborate with backend engineers on data pipelines and infrastructure
Work within solution architecture frameworks to ensure AI integration
Contribute to solution design and technical decision-making
Translate business requirements into technical specifications

Required Skills & Experience

Great experience combining data science with software engineering
Strong expertise in machine learning, with focus on causal ML and probabilistic modelling
Experience developing and implementing knowledge graphs
Proficiency in scaling AI solutions from concept to production
Working knowledge of backend systems, data pipelines, and ETL processes
Familiarity with cloud platforms, particularly Microsoft Azure
Understanding of microservices architecture and distributed systems
Experience with DevOps practices for AI/ML workflows (MLOps)
Strong programming skills in Python and related data science libraries
Demonstrated ability to work within solution architecture frameworks

Preferred Qualifications

Experience with multiple cloud providers beyond Azure
Familiarity with container orchestration (Kubernetes)
Knowledge of graph databases and query languages
Experience with deep learning frameworks
Background in NLP, computer vision, or reinforcement learning
Domain expertise across industries but familiar with Financial Services, Healthcare and Lifesciences, Industrials and Telecommunications and infrastructure would be a plus

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