Product Analyst

Remitly•Arlington, VA

8d•$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 combine rigorous, AI-first analysis with hands-on product ownership. Working closely with cross-functional teams — Product, Engineering, and Marketing — you will analyze customer behavior, help define and prioritize the roadmap, evaluate product experiments, and build the trusted data systems and AI-driven workflows that let the whole team make faster, better decisions. This is not a reporting or support function that exists to service PM requests. It's a builder role with a hard data and AI core, and it's the on-ramp for our next generation of data-driven Product Managers — you'll own a slice of the roadmap, build genuine product judgment, and grow into product leadership over time. You'll leverage your analytical expertise, product judgment, and AI-first tools 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.
Strong technical skills — strong SQL and Python, comfort with data modeling, and a builder's mindset (you'd rather write code to automate a report than pull it by hand).
Fluency with AI-first tools and workflows, and an instinct to reach for them first.
At least 3–4 years of experience in product analytics, product management, customer analytics, or a related quantitative/product role, ideally within fintech, e-commerce, or similar industries.

Responsibilities

Analyze customer behavior across the product lifecycle — acquisition, onboarding, engagement, and retention — using an AI-first approach to identify opportunities that improve the customer experience and inform product decisions.
Own a slice of the product roadmap end to end — from identifying the opportunity, to sizing the impact, to writing requirements or lightweight specs, to partnering with Engineering to ship, to tracking results post-launch.
Build and maintain robust analytical systems — clean data models, dashboards, and self-serve tooling — so Product, Engineering, and Marketing can run their own queries and read their own experiment results without waiting on you.
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. You should be looking for ways to automate yourself out of the routine work so you can spend your time on higher-leverage product problems.
Partner with Product and Engineering to design, run, and interpret A/B tests and experiments — leaning on AI-first workflows to move faster — and use results to guide roadmap prioritization and feature development.
Drive AI-first 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.
Collaborate with Marketing on campaign measurement and attribution as needed, ensuring product and marketing efforts stay aligned.