Principal Applied Scientist

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.