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Job Description

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

Qualifications

Experience with multiple cloud providers beyond Azure Familiarity with container orchestration (Kubernetes) Knowledge of graph databases and query 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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