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- Tasks: Analyse large datasets and apply machine learning to uncover insights.
- Company: Join a forward-thinking company in the heart of Manchester.
- Benefits: Enjoy a competitive salary, 25 days holiday, and health benefits.
- Why this job: Make a real impact by solving complex data problems with cutting-edge technology.
- Qualifications: Studying Data Science or related field with strong AI knowledge.
- Other info: Flexible working options and exposure to industry-standard tools.
The predicted salary is between 13 - 16 £ per hour.
JOB DUTIES & RESPONSIBILITIES:
- 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 visualizations and presentations.
Experience & Education Requirements:
- 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 of 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 visualization 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.
Desirable Skills (Not Required):
- Experience working with natural language processing (NLP) techniques.
- Familiarity with deep learning frameworks such as TensorFlow 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.
What We Offer:
- 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.
AI Placement Analyst (#720888) in Manchester employer: Hirebridge
Contact Detail:
Hirebridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Placement Analyst (#720888) in Manchester
✨Tip Number 1
Network like a pro! Reach out to your university's alumni or professionals in the field. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and data analysis. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to AI and data science. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace AI Placement Analyst (#720888) in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Placement Analyst role. Highlight your experience with machine learning, data analysis, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Be sure to mention any specific experiences that relate to the job description.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills in Python, machine learning, and data visualisation. We love seeing examples of how you've applied these skills in real-world scenarios, so include any relevant projects or coursework.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Hirebridge
✨Know Your Data Inside Out
Before the interview, make sure you’re familiar with the types of datasets you might be working with. Brush up on your data processing and analysis skills, and be ready to discuss how you’ve applied machine learning algorithms in past projects. This will show that you can hit the ground running!
✨Showcase Your Communication Skills
Since you'll need to explain complex data insights to non-technical stakeholders, practice articulating your thoughts clearly. Prepare examples where you've successfully communicated technical concepts in a simple way. This will demonstrate your ability to bridge the gap between data and business objectives.
✨Prepare for Technical Questions
Expect questions about machine learning algorithms, data preprocessing, and feature engineering. Review key concepts and be ready to solve problems on the spot. You might even be asked to walk through your thought process while tackling a hypothetical data challenge.
✨Demonstrate Your Team Spirit
Collaboration is key in this role, so be prepared to discuss your experience working in cross-functional teams. Share examples of how you’ve contributed to team projects and how you handle feedback. This will highlight your ability to work well with others and adapt to different perspectives.
