Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Evaluate AI applications and assess security controls in a global financial services project.
- Company: Join a leading global financial services organisation focused on risk and security.
- Benefits: Enjoy hybrid work with competitive pay of £550 a day for a 6-month contract.
- Why this job: Work at the forefront of AI and security, making a real impact in a dynamic environment.
- Qualifications: Proven experience in AI/ML or data engineering; strong Python skills required.
- Other info: Immediate start available; perfect for tech-savvy individuals passionate about AI and security.
The predicted salary is between 39600 - 59400 £ per year.
Immediate contract for an experienced Data Scientist or Data Engineer with a strong background in Machine Learning (ML) or Artificial Intelligence (AI) to work on a project within a global Financial Services organisation within risk and security. 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 Data Scientist/Engineer 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.
- 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.
- 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).
Data Scientist / Data Engineer employer: Networking People (UK) Limited
Contact Detail:
Networking People (UK) Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist / Data Engineer
✨Tip Number 1
Make sure to showcase your experience with AI and ML in your conversations. Be prepared to discuss specific projects where you've evaluated AI-driven applications or assessed security controls, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Brush up on your knowledge of large language models (LLMs) and AI lifecycle management. Being able to speak confidently about these topics will set you apart, especially when discussing risks and vulnerabilities in AI systems.
✨Tip Number 3
Highlight your communication skills during interviews. Since the role requires translating complex concepts for non-technical stakeholders, be ready to provide examples of how you've successfully communicated technical information in the past.
✨Tip Number 4
Network with professionals in the financial services sector who are involved in AI and security. Attend relevant meetups or webinars to gain insights and make connections that could help you land this role.
We think you need these skills to ace Data Scientist / Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI/ML and data engineering. Focus on relevant projects, especially those involving risk assessment and security controls, to demonstrate your suitability for the role.
Craft a Compelling Cover Letter: Write a cover letter that specifically addresses the key responsibilities mentioned in the job description. Explain how your skills in Python, statistical analysis, and communication can contribute to the company's goals in evaluating AI-driven applications.
Showcase Relevant Projects: Include specific examples of past projects where you assessed AI security controls or worked with large language models. This will help illustrate your hands-on experience and technical expertise to potential employers.
Highlight Communication Skills: Since the role requires translating complex concepts for non-technical audiences, emphasise your ability to communicate effectively. Provide examples of how you've successfully conveyed technical information to diverse stakeholders in previous roles.
How to prepare for a job interview at Networking People (UK) Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with AI and ML, particularly in risk and security contexts. Highlight specific projects where you've evaluated AI-driven applications or assessed security controls, as this will demonstrate your suitability for the role.
✨Communicate Clearly
Since the role requires translating complex concepts for non-technical stakeholders, practice explaining your past projects in simple terms. Use analogies or relatable examples to make your points clear and engaging.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest developments in AI and ML, especially regarding security risks and compliance frameworks. Mention any recent articles or research you've read during the interview to show your commitment to staying informed.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think of examples where you identified vulnerabilities or implemented mitigation strategies, and be ready to discuss your thought process and outcomes.
