AI Placement Analyst

AI Placement Analyst | Student Placement Undergraduate Sandwich Year Programme

• Collect, process, and analyse large datasets to extract meaningful insights.
• Apply machine learning algorithms and statistical models to large datasets to identify trends, patterns, and relationships.
• Collaborate with cross-functional teams to understand business objectives and develop data‑driven solutions.
• Design and implement end‑to‑end machine learning pipelines, from data preprocessing to model training, evaluation, and deployment.
• Document processes, methodologies, and findings in a clear, structured manner.
• Communicate complex data insights and findings to non‑technical stakeholders through visualisations and presentations.

• Currently enrolled in a UK university studying Data Science, Computer Science, Mathematics, Statistics, or a related field with predicted 2:1 or 1st class honours.
• Academic/Industry experience applying AI techniques to solve complex data problems.
• Strong knowledge of machine learning and deep learning algorithms and statistical models, including supervised and unsupervised learning methods.
• Experience with data preprocessing, feature engineering, and data visualisation techniques.
• Proficiency in Python programming, and experience working with large unstructured data.
• Excellent communication skills, with the ability to explain complex concepts to non‑technical stakeholders.
• Strong problem‑solving skills and attention to detail.

• Experience working with natural language processing (NLP) techniques.
• Familiarity with deep learning frameworks such as Tensor Flow or PyTorch.
• Experience with generative AI tools and frameworks (e.g., LLMs, diffusion models).
• Experience building Python microservices with Flask and Docker.
• Knowledge of SQL and database systems.
• Experience with agile development methodologies and version control tools such as Git.

• Competitive placement fixed salary income.
• 25 days + bank holidays per year, private dental & medical, life assurance, pension.
• Working hours 9‑5pm in our Central Manchester offices (hybrid and remote options available).
• Exposure to real‑world business problems and industry‑standard tools.
• Opportunity to work on impactful projects from inception to deployment.

• Internship

• Full‑time

• Human Resources