Multifamily Underwriting Analyst - Irvine, CA — Irvine, CA. Apply via Workday.
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Underwriting Analyst in Canada
6 active opportunities · Updated October 2026
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6 jobs
Explore current underwriting analyst jobs across Canada. Filter by work mode, employment type, experience, department, date posted and distance.
$63.9K – $79.9K/yr
Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations at Brex Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What you'll do As an Underwriting Senior Analyst, your goal is to ensure our underwriting processes run smoothly and efficiently for our cards products. You'll exercise judgment within established underwriting frameworks to resolve moderately complex cases involving multiple contributing factors. This is a role that requires strong communication, time management, and teamwork. You will implement solutions to uplift processes and engage cross-fun
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Capital team is responsible for managing the end-to-end risk strategy for Stripe's lending product. The team is based in the US and Canada, and is composed of curious, driven, and analytical individuals who are passionate about using their skills to shape the future of Stripe. We partner closely with Stripe's engineering, data science, product, and servicing teams to leverage existing platforms, integrate industry best practices, and develop novel solutions to evaluate and manage credit risk. If you are interested in joining a fast-growing organization and applying your experience to shape the future of Stripe, we encourage you to apply. What you’ll do As a key member of the Capital team, you will have the opportunity to shape the future of Stripe's credit policy by driving meaningful changes to the risk and underwriting framework. You will leverage Stripe's vast data assets to formulate your recommendations and work closely with our partners and, where applicable, leverage third-party data. We are a small and lean team, which means you will have the autonomy and the responsibility to manage end-to-end risk initiatives. Responsibilities Architect and implement credit policies based on Stripe's proprietary data and selected industry data to target, price, and size capital products. Utilize your analytical and technical skills to provide credit risk recommendations, deliver insights, and support strategic business decisions. Collabor
Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: SoFi is seeking a highly motivated Staff Data Scientist to join the Marketing Data Science (MDS) team. The MDS team plays a crucial role in enabling data-driven decisions across SoFi's Marketing organization through robust analytics, modeling, experimentation, and measurement. This exciting new role will focus on supporting the development and execution of top-tier marketing strategies specifically within the Direct Mail (DM) channel. The DM channel is a key driver of revenue and new account acquisition for SoFi, encompassing all lending products—including Personal Loans, Home Loans, Student Loan Refinance, In-school Loans, and Credit Cards—as well as Checking & Savings, Small Medium Business Loans, and future products. This position is ideal for someone passionate about utilizing data for problem-solving in a fast-paced environment. It requires direct interface with marketing managers, channel owners, and third-party partners to collaboratively identify opportunities for improvement and enhanced efficiency. What you’ll do: Lead the end-to-end Direct Mail (DM) campaigns, including pre-screened (PS) and invitation-to-apply (ITA) across products. This encompasses identifying the underwriting, marketing and suppression rules, clearly defining the data source and logic, executing the c
Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The team SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first. The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The initial focus of the role will be on Personal Loan but the candidate may get opportunities to work on other lending products in the future. The candidate will be responsible for independently developing and implementing Personal Loan underwriting strategies that meet our risk appetite, monitoring and analyzing the risk trends within the portfolio to provide insights and recommendations for strategy enhancement opportunities. She/he will be part of
$212K – $318K/yr
Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s
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