Product Analyst

Remitly•Arlington, VA

3d•$116,000 - $135,500•Hybrid

About The Position

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: As a Product Analyst at Remitly Borrow, you will play a pivotal role in shaping product and customer strategy, combining rigorous analysis with hands-on product ownership. Working closely with cross-functional teams, including Product, Engineering, and Marketing, you will analyze customer behavior, help define and prioritize the roadmap, evaluate product experiments, and uncover opportunities to improve acquisition, retention, and lifetime engagement. You will leverage your analytical expertise, product judgment, and AI-first tools and workflows to help shape decisions that align with our mission to create a seamless and secure remittance experience for our global customer base. This role reports directly into our Principal Business Manager.

Requirements

A passion for solving customer problems through data, with genuine curiosity about how product decisions shape customer behavior.
3+ years of experience in product analytics, product management, customer analytics, or a product role, ideally within fintech, e-commerce, or similar industries.
Experience owning a product area or initiative — from writing requirements and prioritizing tradeoffs to partnering with Engineering on delivery.
Proficiency in SQL and experience working with large, often messy datasets from multiple sources.
Experience designing and analyzing A/B tests and experiments, with a track record of turning results into product recommendations.
Expertise in data visualization tools such as Tableau or Mode.
Experience with statistical analysis and predictive modeling using Python or R.
Fluency working in an AI-first way — using tools like Claude, Copilot, or ChatGPT to speed up SQL/code writing, synthesize research, and automate reporting — and enthusiasm for adopting new AI capabilities as they emerge.

Nice To Haves

Bonus: experience with marketing attribution modeling or channel performance analysis.

Responsibilities

Analyze customer behavior across the product lifecycle — acquisition, onboarding, engagement, and retention — to identify opportunities that improve the customer experience and inform product decisions.
Help define, prioritize, and scope product improvements, writing requirements or lightweight specs and partnering with Engineering to bring them to life.
Own a slice of the product roadmap end to end — from identifying the opportunity, to sizing the impact, to defining success metrics, to tracking results post-launch.
Partner with Product and Engineering to design, run, and interpret A/B tests and experiments, using results to guide roadmap prioritization and feature development.
Build and maintain dashboards and self-serve reporting tools that give Product, Engineering, and Marketing stakeholders visibility into key product and customer health metrics.
Drive customer segmentation and lifecycle analysis to identify at-risk cohorts, high-value customers, and opportunities for personalization across product and marketing touchpoints.
Represent the voice of the customer in product discussions, translating research and data into clear recommendations for stakeholders and leadership.
Work in an AI-first way — using LLM-based tools, predictive models, and AI-assisted coding/query workflows to accelerate analysis, automate repetitive reporting, and surface insights faster.
Collaborate with Marketing on campaign measurement and attribution as needed, ensuring product and marketing efforts stay aligned.