Data Scientist

General Description

Data Scientist

Hybrid Working – Local Site – 1-2 days a week on site.

Financial Services

All potential candidates should read through the following details of this job with care before making an application.

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. xwzovoh

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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