As a Python Data Analyst you will work closely with the Fraud and Risk team to analyse complex datasets, develop insights and contribute to data-driven decision-making across the business.
The Fraud and Risk department plays a crucial role in protecting the company from financial threats and fraudulent activities. The key responsibilities and functions include fraud prevention and detection, risk assessment and management, and compliance and security.
You will work closely with management to implement reporting structures and data-driven solutions that advance our risk prevention measures.
This is a great opportunity for aspiring data scientists to get hands-on experience and apply their skills to make a difference.
This position is full-time and demands exceptional technical ability, statistical knowledge and data visualisation techniques.
Successful applicants will need to provide proof of eligibility to work in the UK.
Preferred Skills, Qualifications and Experience
- Degree in Computer Science, Statistics, Mathematics, Economics or similar discipline.
- Experience using Python.
- Basic understanding of data science principles and methods.
- Ability to deliver solutions through quantitative research using multiple data sources.
- Self-motivated researching and delivering change within the department.
- Strong analytical and problem solving skills.
- Effective communication with staff and key stakeholders throughout the operation; identifying and undertaking the appropriate course of escalation.
Main Responsibilities
- Collecting, processing, and analysing large datasets using various tools and techniques.
- Developing and maintaining dashboards and other data products.
- Instilling accurate and effective reporting channels.
- Presenting research and analysis in a clear and concise manner.
- Assisting in the creation and implementation of rules-based or machine learning models.
- Collaborating with cross-functional teams to identify business problems and propose data-driven solutions.
The closing date for applications is 23/12/2024.
To apply send a copy of your CV with covering letter quoting the position reference PDAFR1124RD or click on the link to apply.
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