Data Scientist

• 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
• 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

Benefits

• Spend up to $1,000 per year on costs related to continuing education or on travel to countries Remitly serves, allowing you to gain insights to our customer’s journeys

• All of our office spaces offer our employees a place to collaborate and celebrate. With locally sourced artwork and vibrant designs, they create an environment that all can enjoy

• Fill your cup up outside of work and take advantage of our generous paid time off policies, leave policies, and flex working hours to ensure you are able to meet the demands of life outside of work

• Tap into the learning routines, resources and affinity groups Remitly provides to help you further your own DEI journey

• Contribute to the communities we serve through volunteering, employee giving, or civic advocacy

• Remitly provides rich benefit plans intended to cover the needs of our diverse teammates

• We’re looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation

• A degree in data science, statistics, mathematics, operations research, or related field (or equivalent experience)

• Experience designing, running, and analyzing experiments to inform business strategy

• Proficiency creating dashboards and visualizations using tools such as Tableau, Power BI, Mode, or similar technology

• 3 or more years of experience using SQL and Python or R for exploratory data analysis, statistical analysis, and machine learning