Remote Analytics Manager, Full Stack (Fraud Analytics) in Stoke-on-Trent

Remote Analytics Manager, Full Stack (Fraud Analytics) in Stoke-on-Trent

Stoke-on-Trent Full-Time 60000 - 80000 £ / year (est.) Working from home possible
Affirm

At a Glance

  • Tasks: Lead fraud analytics projects and develop strategies to combat fraud using data analysis.
  • Company: Join Affirm, a company transforming credit with transparency and fairness.
  • Benefits: Enjoy remote work flexibility, competitive pay, and opportunities for professional growth.
  • Other info: Collaborative environment with diverse teams and dynamic challenges.
  • Why this job: Make a real difference in the financial industry while working with innovative technology.
  • Qualifications: Bachelor’s degree in a quantitative field and strong analytical skills required.

The predicted salary is between 60000 - 80000 £ per year.

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

  • Fraud Strategy: Comfort using Python or other scripting languages for data analysis.
  • Communication: Ability to build strong cross-functional partnerships and work with a diverse range of teams across the organization. Ability to communicate analyses and recommendations clearly to both technical and non-technical audiences.
  • Multi-tasking: Strong time management skills and the ability to shift focus on a moment's notice to respond to changes in fraud pressure and tactics.
  • Industry knowledge: Working knowledge of the fundamentals of payment processing and an understanding of industry risk trends, including familiarity with risk strategy development.
  • Education: Bachelor’s degree, or local equivalent, in a quantitatively rigorous field like engineering, statistics, math, finance, or economics desired.

Remote Analytics Manager, Full Stack (Fraud Analytics) in Stoke-on-Trent employer: Affirm

At Affirm, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a Remote Analytics Manager, you'll enjoy the flexibility of remote work while being part of a mission-driven team dedicated to transforming the credit landscape. With ample opportunities for professional growth and a commitment to transparency and integrity, Affirm is an excellent employer for those seeking meaningful and rewarding careers in the fintech space.

Affirm

Contact Details:

Affirm Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote Analytics Manager, Full Stack (Fraud Analytics) in Stoke-on-Trent

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those working at Affirm or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.

Tip Number 2

Show off your skills! If you've got experience with Python or data analysis, create a mini-project or case study to demonstrate your abilities. Share it on LinkedIn or during interviews to make a lasting impression.

Tip Number 3

Prepare for the unexpected! In the world of fraud analytics, things can change quickly. Brush up on your time management skills and be ready to discuss how you've handled shifting priorities in past roles.

Tip Number 4

Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your understanding of payment processing and risk trends, and let’s get the conversation started!

We think you need these skills to ace Remote Analytics Manager, Full Stack (Fraud Analytics) in Stoke-on-Trent

Python
Data Analysis
Communication Skills
Cross-Functional Collaboration
Time Management
Adaptability
Payment Processing Knowledge

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of Remote Analytics Manager. Highlight your experience with fraud analytics and any relevant skills in Python or other scripting languages. We want to see how your background aligns with our mission!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about fraud analytics and how you can contribute to our team. Keep it engaging and make sure to connect your experiences to the job description.

Showcase Your Communication Skills:Since you'll be working with diverse teams, it's crucial to demonstrate your ability to communicate complex analyses clearly. Include examples in your application that show how you've successfully communicated with both technical and non-technical audiences.

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 the role. Plus, it shows us you’re keen on joining our team!

How to prepare for a job interview at Affirm

Know Your Analytics Inside Out

Make sure you brush up on your analytics skills, especially in Python or any other scripting languages. Be ready to discuss specific projects where you've used these skills to tackle fraud analytics, as this will show your practical experience and understanding of the role.

Communicate Like a Pro

Since you'll be working with both technical and non-technical teams, practice explaining complex analyses in simple terms. Prepare examples of how you've successfully communicated insights in the past, as this will demonstrate your ability to build strong cross-functional partnerships.

Stay Sharp on Industry Trends

Familiarise yourself with the latest trends in payment processing and fraud risk strategies. Being able to discuss current industry challenges and how they relate to the role will show that you're not just qualified, but also genuinely interested in the field.

Master Time Management

Prepare to showcase your multitasking abilities. Think of instances where you've had to shift focus quickly due to changing priorities, especially in high-pressure situations. This will highlight your adaptability and readiness for the dynamic nature of fraud analytics.