Data Scientist

World Wide Technology (WWT) is a global technology integrator and supply chain solutions provider. Through our culture of innovation, we inspire, build, and deliver business results, from idea to outcome.

World Wide Technology EMEA. has an opportunity available for a Data Scientist or Data Engineer with a strong background in Machine Learning (ML) or Artificial Intelligence (AI) to join our client’s risk and security team. This role is critical in evaluating AI-driven applications and performing in-depth assessments of security controls and vulnerabilities, particularly in the context of large language models (LLMs) and other advanced AI systems.

The ideal candidate will blend deep technical expertise with strong communication skills, capable of translating complex AI and security topics into clear, actionable insights for stakeholders across technical and non-technical teams.

Key Responsibilities
Conduct thorough technical reviews of AI/ML applications to identify potential vulnerabilities and risks.
Assess and evaluate AI security controls, including data integrity, model robustness, explainability and compliance with governance frameworks.
Analyze risks in LLM and ALM (AI Lifecycle Management) environments.
Translate complex AI, ML and security-related concepts for non-technical audiences.
Collaborate with cross-functional teams to recommend and implement mitigation strategies.
Stay up to date on emerging risks in AI/ML systems and continuously evolve the assessment methodology.

Required Qualifications
Proven experience in AI/ML or data engineering, with hands-on application in a risk, compliance or security-focused role.
Strong proficiency in Python and statistical analysis.
Familiarity with LLMs, ML pipeline management and AI lifecycle tools (e.g., MLflow, ModelOps platforms).
Excellent communication and documentation skills for technical and non-technical stakeholders.
Bachelor’s or Master’s degree in Machine Learning, AI, Computer Science, Statistics, Mathematics or a related field.

Preferred Qualifications
Experience working in AI governance, security risk assessment or regulated environments (e.g. finance, healthcare).
Knowledge of responsible AI frameworks or security standards (e.g. NIST AI RMF, ISO/IEC 23894).
Familiarity with cloud-based ML platforms (e.g. AWS SageMaker, Azure ML, GCP AI Platform).