At a Glance
- Tasks: Design and deploy innovative AI solutions that transform business operations.
- Company: Leading organisation in AI-driven automation with a focus on collaboration.
- Benefits: Competitive salary, benefits, and a clear career path into senior roles.
- Other info: Join a research-driven culture with exposure to cutting-edge AI tools.
- Why this job: Work on high-impact projects and push the boundaries of AI technology.
- Qualifications: First-class degree in relevant fields and proficiency in Python and ML frameworks.
The predicted salary is between 72000 - 88000 £ per year.
This organisation is at the forefront of AI-driven automation, building advanced solutions that transform how accountancy, finance, and professional services firms operate. The focus is on combining mathematical rigour with practical AI innovation to deliver technology that enables businesses to work smarter, faster, and with greater accuracy.
As an AI Graduate Scientist, you will design, develop, and deploy cutting-edge AI solutions that push the boundaries of automation and document intelligence. You’ll work closely with a multidisciplinary team of mathematicians, engineers, and domain experts, applying modern techniques in NLP, computer vision, and machine learning to solve complex, real-world problems. This role is ideal for someone with a strong mathematical foundation, a passion for AI research, and a desire to see their work deliver real business impact.
Key Responsibilities
- Research & Development: Investigate and implement advanced AI/ML algorithms, with a focus on document intelligence, information retrieval, and data automation.
- Product Innovation: Contribute to the development of a document intelligence platform using NLP and computer vision to extract, classify, and structure data from complex, unstructured sources.
- Retrieval-Augmented Generation (RAG): Design and implement intelligent retrieval systems, exploring approaches such as GraphRAG and Google ScaNN to improve contextual accuracy.
- Full-Stack AI Deployment: Build, test, and deploy AI-powered bots and web applications on Microsoft Azure, ensuring scalability, security, and performance.
- Enterprise AI Integration: Develop Model Context Protocol (MCP) systems to integrate AI models with enterprise data sources for domain-specific AI interactions.
- Explainable AI: Research and apply model interpretability techniques to ensure AI systems are transparent, reliable, and business-ready.
- Continuous Learning: Stay up to date with cutting-edge AI research and evaluate new methods for practical application.
Skills & Qualifications
- First-class degree (or equivalent) in Mathematics, Computer Science, Artificial Intelligence, or a related discipline.
- Strong mathematical grounding, particularly in algebra, number theory, and statistics.
- Proficiency in Python and experience with major ML frameworks such as PyTorch or TensorFlow.
- Solid understanding of NLP, computer vision, and information retrieval.
- Ability to translate theoretical models into practical, deployable solutions.
- Experience with cloud platforms, ideally Microsoft Azure.
- Knowledge of vector search, RAG pipelines, and document chunking strategies.
- Familiarity with advanced similarity search or vector quantisation techniques.
- Experience deploying AI applications in enterprise environments.
- Interest in explainable AI and model interpretability.
What’s on Offer
- The opportunity to work on high-impact AI projects solving real business problems.
- A collaborative, research-driven culture that values both innovation and rigour.
- Exposure to cutting-edge AI tools, techniques, and research.
- Competitive salary and benefits.
- A clear career path into senior research or engineering roles.
Data Scientist in Glasgow employer: Net Talent Partners
Net Talent Partners is an exceptional employer, offering a dynamic work culture that values innovation and collaboration. With a focus on employee growth, you will have access to professional development opportunities while working in a hybrid model from the vibrant city of Edinburgh, known for its rich history and thriving tech scene. Join us to make a meaningful impact through data management and reporting, all while enjoying a supportive environment that prioritises work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Glasgow
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Net Talent Partners!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist at Net Talent Partners.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Net Talent Partners.
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We think you need these skills to ace Data Scientist in Glasgow
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Net Talent Partners, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Net Talent Partners. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Net Talent Partners
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Net Talent Partners!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
