At Remitly, we help immigrant communities around the world send over $6 billion a year to their loved ones. Sending money is faster, easier, and costs less with our all-digital money transfer platform. Our vision is to transform the lives of immigrants and their families by providing the most trusted financial service products on the planet. At Remitly, your work has a direct and positive impact on people around the globe. Your work matters, every day.

We are looking for an exceptional Machine Learning Engineer to join our global ML team to work on data products that underpin our business. Our ML team currently maintains systems that set our FX rates for customers, detect bad actors using our product, and forecast volume to inform our currency trading strategy. This role will focus on the Pricing and Treasury spaces where you will develop models that are used to trade and price tens of millions of dollars worth of volume every day.  

In this role, you will:

• Build production systems that set FX rates to customers in real time.
• Be a subject matter expert in Pricing and Treasury, and a thought leader with respect to pricing choices throughout Remitly. In this capacity you will partner with Economists, Analysts, and Engineers to build the strategies and products that power our pricing engine. 

• You will provide insightful statistical and econometric analysis that extracts value from complex datasets and achieves targeted outcomes. 
• Have a significant impact on Remitly’s bottom line. Your work will impact our customer facing product and dictate the exchange rates customers receive on transactions every day. As an exceptional business thinker, you will also provide analytical expertise and judgement to other teams including Treasury and Marketing.

You are:

• Outcome oriented. All models start and end with a business problem. You enjoy seeing and measuring the results of your work and are excited to build products with a large impact to the company. 
• Economically minded. We approach many problems from a microeconomic perspective. You enjoy finding the simplest form for a problem and aligning your underlying models with business intuition and economic theory. 
• Energetic. You continually exhibit high energy and an ability to stay positive under pressure. We should be a self-starter, able to work independently, as well as work in a team-oriented and fast paced environment.

• Curious. You ask why, and you question every assumption. If you've ever said "oh, I just did it that way because [Important Person] said so," you won't do well here. We need you to probe assumptions, question the status quo, and follow up on unexpected data results.

• Confident in your data and ideas. You can explain the method to your analysis and independently validate your results. Once the data supports your ideas, you're willing to advocate your recommendations to any stakeholder that needs to buy-in (fortunately for you, we're happy to rally behind your great idea).

Successful candidates should have:

• An MS or PhD in Computer Science, Economics, Statistics, Applied Mathematics or a related area
• 4+ years of work experience building production ready systems, with at least 2+ years applying statistics and machine learning that resulted in data-driven business impact.
• Solid knowledge of both the theory and application of ML algorithms.
• Proficiency with systems design and data processing. Candidates should have hands on experience with Python, ML libraries (e.g., scikit-learn, scipy, numpy, matplotlib, pandas etc), and SQL. Experience with AWS, Scala, Spark, and Hadoop are also sought but not necessary. 
• Strong knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Ability to present complex concepts in a clear narrative that influences stakeholders to take action.
• You are curious, love to continuously improve and exhibit the aptitude to learn quickly.
• You love making a difference.