Data Scientist

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:

Under the supervision of the Senior Data Scientist, the Data Scientist will work on developing credit and fraud risk models, utilizing advanced machine learning, statistical and quantitative methodologies. Telecommuting is available from anywhere in the United States based on manager approval.

You Will Work On:

• Utilizing programming skills in Python to develop, implement, test, and maintain credit and fraud risk models, ensuring accuracy and efficiency. 

• Designing, conducting, and analyzing appropriate types tests (e.g. A/B/n, multi-variate, population) that drive Remitly’s lending strategic choices and models.

• Contributing to assessing impact of our lending strategies and the development of the Customer Lifetime Value models with advanced modeling techniques. 

• Collaborating with cross-functional teams to enhance existing credit underwriting and fraud mitigation strategies. 

• Conducting in-depth statistical analyses and provide insights into market risk factors, trends, and potential areas of improvement. 

• Investigating and following industry trends, regulations, and best practices in quantitative analytics, as well as credit and fraud risk modeling.

You Have:

• Position requires a Master’s degree in Statistics, Data Science, Data Analytics, Mathematics, or a related quantitative field.

• 2 years of experience with data and business analysis. 

• 1 year of experience applying advanced machine learning and statistical modeling techniques, including regression, logistic regression, decision trees, and random forest.

• 1 year of experience solving business problems using statistical and econometric modeling techniques.

• 1 year of experience developing and maintaining Power BI dashboards to monitor key performance indicators (KPIs).

• 1 year of experience communicating complex quantitative concepts to non-technical stakeholders.

• 1 year of experience analyzing time-series data, performing multivariate analysis, and conducting causal inference.

• 1 year of experience designing and executing statistical experiments using A/B testing frameworks, experimental design, power analysis, and non-parametric statistics.

• 1 year of experience building and automating ETL pipelines using tools such as Azure Data Factory.

• 1 year of experience monitoring and troubleshooting data pipelines and analytical workflows in production environments.

• 1 year of experience utilizing Azure Databricks, MySQL, PostgreSQL, Python, R, SQL, Tableau, Power BI, SQL Server Management Studio (SSMS), Azure Data Factory, Azure Repos, PySpark, Jupyter Notebooks, and advanced Excel.

Compensation Details. The starting base salary range for this position is typically $136,000.00 - $204,000.00. In the U.S., 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.

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Our Benefits:

• Flexible paid time off

• Health, dental, and vision + 401k plan with company matching

• Paid parental, medical, military and family care leave

• Mental Health & Family Forming Benefits

• Employee Stock Purchase Plan (ESPP)