Data Analyst Fraud

Job Description:

Remitlys vision is to transform lives with trusted financial services that transcend borders. Since 2011 we have been tirelessly delivering on our promises to people who send money around the world. Today we are reimagining global financial services and building products that extend beyond traditional barriers to give customers access to more of the services they need no matter where they call home. Join over 2700 employees worldwide who are growing their careers with purpose and connection with our customers while having a positive impact on millions of people around the globe.

About the Role:

As a Data Analyst Fraud you will be part of Remitlys Identity & Trust Analytics Team and will report to one of our Directors of Analytics. You will apply data science and analytics techniques to drive rapid rational decisionmaking for Remitlys EU & International business. You will understand internal fraud systems understand regional differences/priorities and customise solutions for various regions. Youll be tightly integrated with Remitlys Business Management Function and collaborate on regional solutions. You will relentlessly improve the experience for good customers by partnering with program and product managers engineers analysts and designers. This is a hybrid role that requires 23 days a week in the London office.

You Will:

• Become an expert on Remitlys Payments Fraud (Scams Chargebacks Promo Abuse) data experience policy and regulatory requirements
• Build a unified understanding of how our data customer experiences and goals align
• Create metrics to balance risk vs. reward performance of systems and operational effectiveness
• Collaborate with Business Management to continuously improve customer experience and deliver on business goals
• Design experiments read A/B tests and perform ad hoc analyses
• Formulate hypotheses design and evaluate product experiments
• Generate insights and help define & execute longer term product strategies and roadmaps across multiple product teams

You Have:

• 2 yrs in an analyst role or similar professional experience in risk fraud fintech operations marketing
• Experience in any type of adversarial analysis such as risk fraud trust & safety is preferred
• Bachelors degree in mathematics engineering economics or another quantitative field (or equivalent additional experience)
• 2 yrs of experience using SQL for analysis (Python R statistical analysis and modelling a bonus)
• Foundational statistical knowledge
• Experience distilling business problems from discussions developing hypotheses building an analytical framework carrying out an analysis and writing a clear recommendation
• Strong data communication skills including data visualisation technical writing and business writing
• Experience finding creative solutions within the constraints of complex systems and policies

#LIHybrid

Our Benefits:

• Paid Vacation Days
• Health insurance
• Commuter benefit
• Employee Stock Purchase Plan (ESPP)
• Mental Health & Family Forming Benefits
• Continuing education and corridor travel benefits

We are committed to nondiscrimination across our global organization and in all of our business operations. Employment is determined based upon personal capabilities and qualifications without discrimination on the basis of race creed color religion sex gender identification and expression marital status military status or status as an honorably discharge/veteran pregnancy (including a womans potential to get pregnant pregnancyrelated conditions and childbearing) sexual orientation age 40 and over) national origin ancestry citizenship or immigration status physical mental or sensory disability (including the use of a trained dog guide or service animal) HIV/AIDS or hepatitis C status genetic information status as an actual or perceived victim of domestic violence sexual or stalking or any other protected class as established by law.

Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.