Audit Analytics Scientist: ML/NLP & Risk Insights in London

Audit Analytics Scientist: ML/NLP & Risk Insights in London

London Full-Time 50000 - 70000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Analyse data using ML and LLMs to enhance audit processes.
  • Company: Subsense Inc., a forward-thinking company in London.
  • Benefits: Full-time role with opportunities for innovation and growth.
  • Other info: Collaborative environment with a focus on data-driven tools.
  • Why this job: Join a dynamic team and make a real impact on risk assessments.
  • Qualifications: Bachelor's or Master's degree in a relevant field, strong stats and ML skills.

The predicted salary is between 50000 - 70000 Β£ per year.

Subsense Inc. is looking for a data scientist in London to engage in audits by analyzing data with traditional machine learning and Large Language Models (LLMs). You will work collaboratively with stakeholders on risk assessments and train auditors to use data-driven tools.

The ideal candidate should hold a Bachelor's or Master's degree in a relevant field and have a strong foundation in statistics and machine learning. This full-time role offers opportunities to innovate within the Group Internal Audit team.

Audit Analytics Scientist: ML/NLP & Risk Insights in London employer: Subsense Inc.

Subsense Inc. is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. Employees benefit from continuous professional development opportunities, allowing them to enhance their skills in cutting-edge technologies like machine learning and NLP. With a focus on data-driven insights and risk assessments, team members are empowered to make meaningful contributions while enjoying a supportive environment that values growth and creativity.

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Contact Details:

Subsense Inc. Recruitment Team

We think you need these skills to ace Audit Analytics Scientist: ML/NLP & Risk Insights in London

Communication Skills
Python
SQL
Problem-Solving Skills
Automation
Data Engineering
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