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- Tasks: Analyse complex datasets and build dashboards to enhance fraud risk strategies.
- Company: Leading fraud prevention firm with a focus on data-driven insights.
- Benefits: Generous compensation and fully remote work environment.
- Why this job: Join a team making a real impact in fraud prevention using your data skills.
- Qualifications: 7+ years in data roles, strong SQL and Python skills, fraud/risk experience.
- Other info: Opportunity to work remotely while contributing to meaningful projects.
The predicted salary is between 43200 - 72000 £ per year.
A prominent fraud prevention firm is seeking a data-driven professional to enhance the performance of risk strategies. The ideal candidate will analyze complex datasets, build dashboards, and work with stakeholders to make data-driven decisions.
Requirements include:
- Over 7 years in data-centric roles
- Strong SQL and Python skills
- Experience in the fraud/risk domain
This position offers generous compensation and a fully remote work environment.
Data Scientist, Fraud Risk & Insights (Remote) employer: Sardine
Contact Detail:
Sardine Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, Fraud Risk & Insights (Remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the fraud prevention space on LinkedIn or at industry events. We can’t stress enough how personal connections can lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those related to fraud risk. This will give potential employers a taste of what you can do with SQL and Python.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. We recommend practising how to explain your thought process when analysing datasets and making decisions.
✨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, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist, Fraud Risk & Insights (Remote)
Some tips for your application 🫡
Show Off Your Data Skills: Make sure to highlight your experience with SQL and Python in your application. We want to see how you've used these skills in real-world scenarios, especially in fraud or risk contexts.
Tailor Your Application: Don’t just send a generic CV! We love it when candidates customise their applications to reflect the job description. Mention specific projects or experiences that align with enhancing risk strategies.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see your qualifications and fit for the role.
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’re considered for this exciting opportunity in our remote team!
How to prepare for a job interview at Sardine
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to fraud risk. Brush up on your SQL and Python skills, and be ready to discuss how you've used them in past roles. Prepare examples of how your data analysis has led to actionable insights.
✨Showcase Your Dashboard Skills
Since building dashboards is part of the role, come prepared with examples of dashboards you've created. Be ready to explain the thought process behind your design choices and how they helped stakeholders make informed decisions.
✨Understand the Fraud Landscape
Familiarise yourself with current trends and challenges in the fraud prevention industry. This will not only show your passion for the field but also help you engage in meaningful conversations with interviewers about potential strategies.
✨Prepare for Stakeholder Scenarios
Think about times when you’ve had to work with different stakeholders. Prepare to discuss how you communicated complex data insights to non-technical audiences and how you ensured their needs were met in your analyses.
