Data Scientist

6 days ago

StainesuponThames, Surrey, United Kingdom Dabster Full time
About the Role

We are seeking a highly skilled Data Scientist to join our Risk Intelligence Engineering function at Dabster. As a key member of our team, you will play a crucial role in shaping the future of risk intelligence and financial services.

Key Responsibilities
  • Research and identify Artificial Intelligence (AI), Large Language Models (LLMs), and Machine Learning (Client) methods and algorithms to solve specific problems within Risk Intelligence.
  • Implement these methods and devise appropriate test plans to validate and compare the different approaches.
  • Identify new applications of AI, LLMs, and Client in the context of our extensive sets of content and data.
  • Explore existing data for insights and recommend additional sources of data for improvements.
About the Team

Our team is a global group of engineers who use Machine Learning to solve problems along the entire Lifecycle of Innovation, with a strong focus on new capabilities and approaches to existing problems. We are a collaborative and open team that values excellence and innovation.

Requirements
  • Advanced degree in Computer Science, Statistics, Technology, or Engineering, or equivalent work experience.
  • Minimum years of industry experience with years of proven track record in the application of AI, Client, and NLP.
  • Excellent programming skills (Python, Java, and R).
  • Good communication & presentation skills: connecting people, gathering data & information across business unit boundaries, and telling & selling the story are no problem for you.
Preferred Qualifications
  • Excellent understanding of Data Science Theory, LLMs, Client, NLP, and statistical methodologies in a data analytics environment.
  • Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation.
  • Experience with search engines, web scraping, data classification algorithms, recommendation systems, and relevance evaluation methodologies.

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