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For Companies At a Glance
- Tasks: Join a team to develop a GenAI-Powered digital assistant and create intelligent conversational agents.
- Company: Leading banking client in the financial services sector with a focus on innovation.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact by leveraging cutting-edge NLP techniques and data visualisation skills.
- Qualifications: Expertise in NLP, Python, and data visualisation tools required.
- Other info: Collaborative environment with exciting projects and career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Hybrid Working – Local Site – 1-2 days a week on site.
Financial Services
Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be working on GenAI-Powered Digital Assistant programme.
What you’ll do
- Collaborate with cross-functional teams to develop and enhance our GenAI-Powered smart digital assistant.
- Leverage your expertise in NLP and transformer architectures to create intelligent conversational agents.
- Dive into the world of traditional NLP techniques and stay ahead of the curve.
- Apply a strong understanding of fundamental concepts - statistics, linear algebra, calculus, regression, classification, and time series analysis – to extract valuable insights from data.
- Be the driving force behind our data visualisation efforts – whether it's Tableau, Power BI, or Cognos you’ll create compelling visualisations that bring data to life.
- Contribute to the development of a fantastic visualisation layer for analytics, making complex insights accessible and actionable.
Key Skills and Experience
- NLP Mastery
- Proficiency in LLMs and transformer architecture.
- Deep understanding of traditional NLP techniques.
- Data & Visualisation
- Solid grasp of data visualisation tools (Tableau, Power BI, Cognos, etc.)
- Proficiency in Python visualisation libraries (Matplotlib, Seaborn).
- SQL for data extraction and manipulation.
- Experience working with large datasets.
- Technical Skills
- Proficiency in cloud computing and python programming.
- Familiarity with Python libraries like Pandas, NumPy, scikit-learn.
- Experience with cloud services for model training and deployment.
- Machine Learning Fundamentals
- Statistical concepts for robust data analysis.
- Linear algebra principles for modelling and optimisation.
- Calculus for optimising algorithms and models.
- Predictive modelling techniques for regression and classification.
- Time series analysis for handling time-dependant data.
- Deep learning and neural networks.
- LLM Operations
- Expertise in managing and operationalising large language models.
- Experience in deploying models on cloud platforms (e.g. AWS, SageMaker, Google AI Platform, IBM Watson).
Data Scientist in England employer: Impellam Group
Contact Detail:
Impellam Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in England
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the hunt for a Data Scientist role. You never know who might have the inside scoop on openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP and data visualisation. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with transformer architectures and large datasets. Practise explaining complex concepts in simple terms – it’s all about making your insights accessible!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for talented Data Scientists like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Scientist in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with NLP, transformer architectures, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of your work, especially those involving data visualisation tools like Tableau or Power BI. We love seeing how you've brought data to life in past projects, so don’t hold back!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and experiences. We appreciate a well-structured application!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Impellam Group
✨Know Your NLP Inside Out
Make sure you brush up on your knowledge of Natural Language Processing (NLP) and transformer architectures. Be ready to discuss specific projects where you've applied these techniques, as well as any challenges you faced and how you overcame them.
✨Showcase Your Data Visualisation Skills
Prepare to demonstrate your proficiency in data visualisation tools like Tableau or Power BI. Bring examples of your work that highlight how you've turned complex data into compelling visuals, and be ready to explain your thought process behind those designs.
✨Brush Up on Your Statistics and Maths
Since the role requires a strong understanding of statistics, linear algebra, and calculus, make sure you're comfortable discussing these concepts. You might be asked to solve problems on the spot, so practice explaining your reasoning clearly and concisely.
✨Familiarise Yourself with Cloud Platforms
As cloud computing is a key part of this role, ensure you know the ins and outs of deploying models on platforms like AWS or Google AI. Be prepared to talk about your experience with these services and how you've used them in past projects.
