Job Description:At Remitly, we believe everyone deserves the freedom to access, move, and manage their money wherever life takes them. Since 2011, we've tirelessly delivered on our promise to customers sending money globally, providing secure, simple, and reliable ways to manage their money, ensuring true peace of mind. Whether it's supporting loved ones back home, growing a business across continents, or pursuing new opportunities abroad, we're not just here to move money- we're here to move our global customers forward.
We're looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation. If that's you and you're ready to do the most meaningful work of your career-we invite you to join over 2,800 passionate Remitlians worldwide who are united by our vision to transform lives with trusted financial services that transcend borders.
About the Role:The Trust Machine Learning team protects Remitly's customers by developing intelligent systems that prevent fraud. These systems assess the risk of every transaction and customer interaction, while minimizing the impact on user experience and customer trust.
As an embedded data scientist, you will understand fraud trends, uncover new fraud signals, and use data to optimize our risk decision policies.
You Will:- Discover and deliver fraud signals that improve model performance to target and prevent first-party fraud, consumer fraud, and unwanted activity
- Manage and assess risk decision policies that improve automated fraud prevention outcomes, balancing risks with operational and customer impacts
- Design metrics and dashboards that communicate fraud model efficacy to business partners
- Design and conduct A/B experiments to assess and understand the impact of fraud decision policy changes
- Partner with machine learning engineers to ensure features are well-integrated and optimized for production models
You Have:- 3 or more years of experience using SQL and Python or R for exploratory data analysis, statistical analysis, and machine learning
- Proficiency creating dashboards and visualizations using tools such as Tableau, Power BI, Mode, or similar technology
- Experience designing, running, and analyzing experiments to inform business strategy
- A degree in data science, statistics, mathematics, operations research, or related field (or equivalent experience)
Compensation Details. The starting base salary range for this position is $120,000-$150,000. In Canada, Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role.
Our Benefits- Four weeks vacation
- Health Benefits
- Mental Health & Family Forming Benefits
- RRSP plan with company match
- Employee Stock Purchase Plan (ESPP)
- Life Insurance & Disability
- Continuing education and travel benefits
Our Connected Work Culture: Driving Innovation, TogetherAt Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster. For corporate team members, we have an in-office expectation of at least 50% of the time monthly, typically achieved by coming in three days a week. This creates a consistent, meaningful overlap that supports team norms and business needs. Managers also have the flexibility to set higher expectations based on their team's specific needs. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.
Remitly is an E-Verify EmployerAt Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.
Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
