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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 model, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact in the exciting world of AI and data science while collaborating with talented teams.
- Qualifications: Expertise in NLP, Python programming, and data visualisation tools required.
- Other info: Work on cutting-edge projects with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Overview
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.
Responsibilities
- 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.
- 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.
- 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.
- 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.
- 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 - Lorien Impellam eFinancialCareers employer: Notjustlabcoats
Contact Detail:
Notjustlabcoats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Lorien Impellam eFinancialCareers
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working at Lorien or similar companies. A friendly chat can open doors and give you insider info that could help you stand out.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP and data visualisation. Share it during interviews or on platforms like LinkedIn to grab attention.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and machine learning concepts. Practice coding challenges and be ready to discuss your thought process—it's all about showing how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Scientist - Lorien Impellam eFinancialCareers
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 data visualisation tools like Tableau or Power BI. We want to see how your skills align with 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 working on GenAI-Powered projects and how your background makes you a perfect fit. Let us know what excites you about the role!
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, we love seeing practical examples of your skills in action!
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. Plus, it helps us keep everything organised!
How to prepare for a job interview at Notjustlabcoats
✨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 previous work that highlight how you've turned complex data into compelling visual stories that drive insights.
✨Brush Up on Your Maths
Since the role requires a strong understanding of statistics, linear algebra, and calculus, be prepared to answer technical questions that test your knowledge in these areas. Practise explaining these concepts in simple terms, as you may need to communicate them to non-technical team members.
✨Familiarise Yourself with Cloud Platforms
As cloud computing is a key part of this role, make sure you know the ins and outs of deploying models on platforms like AWS or Google AI. Be ready to discuss any hands-on experience you have with these services and how you've used them in past projects.
