Upstart Verified

FinTech, Artificial Intelligence, Lending

Principal Applied Scientist

United States |, United StatesRemoteFull TimePrincipal$238,400–$330,200 /yrPosted 11 days agoVisa sponsorship available

Is this role right for you?

Upload your resume and get a skill-by-skill breakdown — see exactly where you match, where you're close, and what to highlight. Not a mystery percentage.

Get a tailored resume highlighting what this role needs.

Role summary

Upstart is seeking a Principal Applied Scientist to define the long-term technical direction for offer optimization and conversion modeling systems. This high-leverage role involves structuring ambiguous problems, designing solutions that consider downstream effects and marketplace dynamics, and driving technical alignment across multiple teams. The work sits at the intersection of operations research, optimization, causal machine learning, and production decision systems. The ideal candidate will have 8+ years of experience deploying ML models at scale, a strong background in statistics and optimization, and experience leading cross-functional technical initiatives. Preferred qualifications include a PhD, experience in offer optimization, fintech, and serving as a principal-level technical lead.

About Upstart

At Upstart, 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 1,800 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 (opening Summer 2026), 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:

Upstart’s Growth and Marketplace Optimization teams are responsible for building the decision systems that determine how offers are presented, optimized, and evolved across the customer journey. These systems sit at the intersection of machine learning, optimization, pricing, marketplace dynamics, and borrower behavior. The work spans partner channels, onsite experiences, and marketplace optimization, with the goal of improving conversion, borrower experience, lender surplus, and overall marketplace efficiency. As these systems continue to evolve, the organization is investing in a more unified technical vision that connects decision-making across stages rather than optimizing individual components in isolation.

The Role:

As a Principal Applied Scientist at Upstart, you will help define the long-term technical direction for some of Upstart’s most important offer optimization and conversion modeling systems. You will work across multiple teams to define how conversion modeling, offer optimization, and system design should fit together, ensuring models and optimization systems account for downstream effects, marketplace constraints, and customer outcomes.

This role is intentionally broad and high leverage. You will help structure ambiguous problem spaces, design solutions that account for interactions across multiple stages of the customer journey, and provide technical oversight to ensure work across multiple teams converges toward a coherent long-term vision. The work sits at the intersection of operations research, optimization, causal machine learning, and production decision systems.

How you’ll make an impact:

Define the technical vision for how offer decisioning systems should interconnect across partnerships, always-on systems, and marketplace optimization

Build and guide conversion modeling approaches that optimize decisions across multiple stages of the customer journey rather than in isolated local steps

Ensure models and decision policies at one stage account for downstream impacts, business constraints, and later-stage optimization opportunities

Design interfaces between decision systems and optimization or constraint-specification components

Drive cross-functional technical alignment across teams that currently own adjacent pieces of the problem

Scope and lead large, ambiguous initiatives that require both deep modeling judgment and strong systems thinking

Partner with scientists, engineers, and cross-functional stakeholders to translate analytical insights into durable production approaches

Help ensure ongoing work across domains progresses toward a unified architecture and decisioning strategy

Contribute directly to implementation and experimentation efforts, including prototyping models, reviewing code, and helping teams operationalize new approaches in production environments.

Minimum Qualifications:

Advanced degree in a quantitative field such as statistics, mathematics, economics, computer science, operations research, or a related discipline

8+ years of experience building and deploying machine learning models into production at scale

Experience with optimization, operations research, or constrained decision-making problems

Working knowledge of causal inference or causal machine learning

Strong grounding in statistics and probability

Experience leading large cross-functional technical initiatives with multiple stakeholders

Experience working across multiple technical teams to align approaches, define interfaces, and move toward a shared vision

Experience solving real-world machine learning or data science problems in a high-impact production environment

Preferred Qualifications:

PhD in operations research, statistics, economics, computer science, or another quantitative field

Experience with offer optimization, pricing systems, marketplace optimization, or related decisioning systems

Experience with end-to-end modeling from problem framing through productionization

Experience in fintech, lending, marketplaces, or other domains where decisions must account for downstream constraints and business tradeoffs

Experience serving as a principal-level technical lead across multiple teams or product areas

Experience mentoring other senior scientists or raising the technical bar across an organization

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.

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

Time zone requirements The team operates on the East/West coast time zones.
At Upstart, 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, Upstart 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, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).
United States | Remote - Anticipated Base Salary Range
$238,400—$330,200 USD
At Upstart, 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, Upstart 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, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).
Canada | Remote - Anticipated Base Salary Range
$220,200—$277,000 CAD
What you'll love

At Upstart, our benefits 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 Upstart 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 (opening Summer 2026!)

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

Upstart 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 candidate_accommodations@upstart.com

https://www.upstart.com/candidate_privacy_policy

Sample Upstart interview questions

1
Diameter of a Binary Tree Find the diameter of a binary tree. Input: root = [1,2] Output: 1 Explanation: The longest path is simply the single edge connecting the root node to its only child.
codingmedium
2
Connected Components in an Undirected Graph Determine the number of connected components in an undirected graph. Input: n = 4, edges = [[0,1],[2,3]] Output: 2 Explanation: The graph is split completely evenly into two distinct isolated components: nodes {0,1} and nodes {2,3}.
codingmedium
3
Split Array into Consecutive Subsequences Split an array into consecutive subsequences. Input: nums = [1,2,3,4,4,5] Output: FALSE Explanation: The numbers can form [1,2,3,4], but the remaining leftover group [4,5] is too short to form a valid sequence of length 3.
codingmedium
4
Pacific and Atlantic Water Flow Calculate water flow from a matrix to the Pacific and Atlantic oceans. Input: heights = [[2,1],[1,2]] Output: [[0,0],[0,1],[1,0],[1,1]] Explanation: All cells can flow to both oceans because water can move to adjacent cells of equal or lower height or directly off the edges.
codingmedium
5
Unique Combinations that Sum to a Target Find all unique combinations in an array that sum to a target. Input: candidates = [2,4,6], target = 6 Output: [[2,2,2], [2,4], [6]] Explanation: Uses backtracking to find all valid combinations that sum to 6, allowing for explicitly repeated elements.
codingmedium

Sign up for a personalized interview prep pack tailored to this role.

Ready to apply?

You'll be redirected to Upstart's application page.