Senior ML/AI Engineer (Fraud prevention)
We are currently recruiting a Senior Machine Learning/AI Engineer with a focus on Fraud prevention for a client who is a leading global tech and telecommunications multinational.
Our client is currently conducting all interviews online and are onboarding all new workers remotely.
Job Reference: BBBH 21815
As a Senior Machine Learning/AI Engineer you will work in the Cybersecurity team and report to the Fraud Prevention Manager. Your role will mainly be to develop and leverage innovative machine learning solutions to solve complex sets of problems and applications. By analysing and detecting patterns in vast amounts of data, you will have a good understanding of machine learning life cycle-algorithms, data structures and design patterns.
We are looking for talented and passionate Software Engineers who are proactive in identifying problems and have the logical thought process and skills to solve them. There will be many opportunities to explore new tech stacks and to work on advanced technologies. As part of the wider Security team, you will have support from different areas and many technical experts in different domains.
Key Responsibilities
- Ability to design and develop machine learning algorithms.
- Discover, design, and develop analytical methods to support novel approaches of data and information processing.
- Identify and apply appropriate methods to process and analyse large datasets of labelled and unlabelled records and discover new valuable insights for the system.
- Provide support on other parts of the system (not limited to Machine Learning).
- Conduct software performance analysis, scaling, tuning and optimisation.
- Review and contribute to improve current software and system architecture for stability and to optimize performance.
- Research & development of fraud detection solution.
Requirements
- Minimum 5 years of experience
- Degree in quantitative field (e.g., Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related fields).
- Be able to solve analytical problems and build models in different programming language (i.e. Python, SQL, Java, Scala)
- Familiar with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering and regression.
Still interested in this opportunity?
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