Data Scientist

Impellam Group
City of London
3 weeks ago
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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 smartdigital 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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