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- Tasks: Analyse data to identify and prevent application fraud, making a real impact.
- Company: Join NewDay, a diverse and inclusive company dedicated to protecting customers.
- Benefits: Full-time role with opportunities for growth and a supportive work environment.
- Why this job: Use your analytical skills to combat fraud and protect financial integrity.
- Qualifications: Experience with SQL/SAS and familiarity with fraud prevention tools required.
- Other info: Dynamic team culture with a focus on collaboration and innovation.
The predicted salary is between 28800 - 48000 £ per year.
As a Application Fraud specialist you’ll use your expertise in analytics to help protect NewDay from financial losses caused by fraudulent activity. With your knowledge of data mining and data visualisation, you’ll analyse large data sets using best in class tools to identify patterns indicating fraudulent behaviour. You’ll then work collaboratively with the team and wider business to develop and implement strategies to prevent against it. This is a fast paced and rewarding role that requires a keen eye for detail and an ability to adapt to changing fraud landscapes. Ultimately, you’ll have the opportunity to make a real difference to our company’s success while helping to protect our customers from financial harm.
How You'll Contribute
- Identify emerging application fraud threats and design effective, data driven strategies to mitigate risk
- Collaborate closely with internal stakeholders and external partners to prevent and reduce application fraud
- Analyse large and complex data sets to develop and implement robust fraud prevention strategies
- Provide clear, actionable insights to identify optimisation opportunities across fraud detection and prevention systems.
We're looking for these essential Skills
- Strong hands-on experience with SQL and/or SAS to interrogate data and uncover fraud signals
- Familiarity with fraud prevention platforms such as Hunter, ThreatMetrix and Featurespace
- Proven capability in rule optimisation and machine-learning model validation
- Solid understanding of code deployment, version control, repositories and automated workflows
- Confidence using data visualisation tools like Power BI to tell clear, compelling stories with data
It's a plus if you also have these skills
- Exposure to Python for data analytics
- Experience within the credit card and wider financial services domain
At NewDay, we value all types of diversity. We’re an equal opportunity employer and believe that our differences create a vibrant, authentic working culture. We want all our colleagues to feel able to bring their whole selves to work. We don’t discriminate on the basis of protected characteristics or identities. We make sure that every job is crafted to be inclusive and that people with disabilities or caring responsibilities can take part in the application and interview process. Tell us if you need accommodations: We’ll put reasonable adjustments in place to support you. We work with Textio to make our job design and hiring inclusive.
Application Fraud Specialist employer: NewDay Ltd
Contact Detail:
NewDay Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Application Fraud Specialist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions related to fraud analysis and data interpretation. We recommend doing mock interviews with friends or using online platforms to get comfortable with your responses.
✨Tip Number 3
Showcase your skills! Create a portfolio that highlights your experience with SQL, SAS, and any fraud prevention tools you've used. This will give you an edge and demonstrate your hands-on expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at NewDay.
We think you need these skills to ace Application Fraud Specialist
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with SQL, SAS, and any fraud prevention platforms you've used. We want to see how your skills can help us tackle application fraud head-on!
Tell a Story with Data: Use data visualisation tools like Power BI to present your insights clearly. We love compelling stories backed by data, so don’t hold back on showcasing your analytical prowess!
Tailor Your Application: Read through the job description carefully and tailor your application to match our needs. We appreciate when candidates take the time to align their experiences with what we’re looking for.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at NewDay Ltd
✨Know Your Data Tools
Make sure you brush up on your SQL and SAS skills before the interview. Be ready to discuss how you've used these tools in the past to uncover fraud signals. Having specific examples will show that you can hit the ground running.
✨Understand Fraud Prevention Platforms
Familiarise yourself with platforms like Hunter, ThreatMetrix, and Featurespace. If you can, try to get hands-on experience or at least read up on how they work. This knowledge will help you demonstrate your readiness to tackle application fraud effectively.
✨Showcase Your Analytical Skills
Prepare to talk about your experience analysing large data sets. Think of a time when you identified a pattern that led to a successful fraud prevention strategy. Being able to share clear, actionable insights will impress the interviewers.
✨Be Ready for Collaboration
Since this role involves working closely with various stakeholders, be prepared to discuss how you've collaborated in the past. Highlight any experiences where teamwork led to successful outcomes in fraud detection or prevention.