Staff Applied Scientist

About the company

At the company, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence.

As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 3,000 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress.

We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City, you’ll have the support to work in the way that works best for you.

If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you.

The Team

The company’s Unsecured Underwriting Machine Learning team develops and improves the models that inform credit decisions for our unsecured lending products. The team conducts machine learning research, evaluates model performance, and partners closely with Engineering teams to translate promising ideas into scalable  model improvements.

As an Applied Scientist, you will research and implement enhancements to the company’s core unsecured underwriting model. Your work will directly influence credit decisioning and help the team increase the pace of research while maintaining the rigor, reliability, and responsible oversight required of production underwriting models.

As an Applied Scientist in the Unsecured Underwriting Machine Learning team at the company, you will:

• Research machine learning and statistical approaches that improve the predictive performance of unsecured underwriting models.

• Design, implement, and evaluate model enhancements using rigorous experimentation and validation methods.

• Analyze model performance and downstream effects to confirm that proposed changes improve decisioning reliably.

• Partner with various Engineering teams to support technical reviews, implementation, and deployment.

• Translate research findings into clear recommendations, documented methodologies, and production-ready solutions.

Minimum Qualifications

• Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.

• 2+ years of experience conducting machine learning, statistical modeling, or applied quantitative research in an academic or industry setting.

• Experience developing and evaluating machine learning or statistical models using Python.

• Demonstrated knowledge of probability, statistics, and machine learning methods.

• Experience designing experiments or validation analyses to assess model accuracy, reliability, or predictive performance.

Preferred Qualifications

• PhD in a quantitative field.

• Knowledge of supervised learning, model evaluation, and feature engineering techniques.

• Experience working with large or complex datasets and translating research concepts into implemented solutions.

• Ability to balance research velocity with analytical rigor, model reliability, and responsible decision-making.

• Strong written and verbal communication skills, with the ability to clearly explain technical concepts and collaborate effectively with cross-functional teams and stakeholders from diverse backgrounds.

Position location This role is available in the following locations: Remote

Time zone requirements The team operates on the East/West coast time zones.

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S or Canada (outside of Quebec) but are expected to spend high quality time in-person collaborating via regular onsites and in-person meetings. The onsite cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

#LI-REMOTE

#LI-MidSenior

At the company, your base pay is one part of your total compensation package.  The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location–with our “digital first” philosophy, the company uses compensation regions that vary depending on location. Individual pay is also determined by job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

In addition, the company provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).

United States | Remote - Anticipated Base Salary Range

$199,500 — $276,000 USD

What you'll love

At the company, our benefits for full-time employees are designed to support your health, financial well-being, family, and personal growth. Here’s what you can expect:

• Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly

• Retirement benefits to help you plan for the future, including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually (USD in the US, CAD in Canada)

• Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only)

• Comprehensive health coverage designed to support you and your family, including medical, dental, vision, and wellness resources for US and supplemental health coverage for Canada.

• Health Savings Account contributions from the company for eligible plans (US only)

• Income protection benefits, including life insurance and disability coverage for added financial security

• Paid time off, sick leave, and company holidays, in line with local requirements

• Paid family and parental leave to support caregiving and major life moments (duration varies by country)

• Family-centered benefits to support fertility, parenthood, and caregiving needs

• Employee Assistance Program (EAP) offering mental health support and life-centered resources

• Financial wellness resources, including access to financial planning tools and a financial concierge service (US Only)

• Annual wellness allowance to support your physical and emotional well-being and personal development, based on what matters most to you

• Annual productivity allowance to invest in relevant tools and resources you need to do your best work, no matter where you work from

• Connection and community through team events, all-company updates, and employee resource groups (ERGs)

• Onsite perks, including catered lunches and fully stocked micro-kitchens when working from one of our offices in the Bay Area, Austin, Columbus, and New York City

For roles based in Canada, please note that we are not currently able to hire in Quebec.

The company is a proud Equal Opportunity Employer. Just as we are dedicated to improving access to affordable credit for all, we are committed to inclusive and fair hiring practices.

If you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email [link for members]

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