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Data Scientist
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 its 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 mode 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, Sage maker, Google AI Platform, IBM Watson)
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Key Skills
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