Staff Research Scientist
About Upstart
Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than two-thirds of Upstart loans are approved instantly and are fully automated.
Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.
Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!
The Team:
Upstart aims to expand access to credit based on true risk. Upstart’s Machine Learning, Growth Partnerships team builds models used to make loan offers on partner websites such as Credit Karma and NerdWallet, with the goal of expanding Upstart’s user base and driving product growth. The team has a large revenue impact and is critical to Upstart’s success.
As a Staff Research Scientist on this team, you will develop advanced Machine Learning models used to optimize loan offers presented on partner websites. You will design and engineer features that capture relevant signals and predictive patterns from various data sources. You will develop rigorous testing frameworks and methodologies to evaluate model performance, robustness, and reliability. You will collaborate with a variety of stakeholders including ML scientists, engineers, product managers and growth marketers. Your work will drive cross-functional decision making and measurable results.
How you’ll make an impact
- Lead the research, development, and implementation of machine learning models to improve loan offer recommendations on partner websites.
- Collaborate with cross-functional teams including product managers, engineers, and data analysts to identify opportunities and address challenges.
- Utilize state-of-the-art machine learning techniques to optimize model accuracy and conversion rates.
- Mentor junior team members, contribute to knowledge sharing initiatives, and foster a culture of continuous learning and innovation within the team.
Minimum Qualifications
- Advanced degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Proven track record of 5+ years of experience in applied machine learning, data science, or related roles.
- Expertise in Python, and proficiency in machine learning frameworks (e.g., XGBoost, PyTorch, scikit-learn)
- Strong understanding of statistical modeling, and model development principles.
Preferred Qualifications
- Expertise in designing and implementing end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and evaluation.
- Experience with large-scale data processing and distributed computing platforms.
- Excellent communication skills with the ability to effectively collaborate with cross-functional teams and convey complex technical concepts to non-technical stakeholders.
- Demonstrated proficiency in mentoring junior team members and offering technical leadership to drive team performance and growth.
- Experience in the fintech industry.
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 but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.
What you'll love:
- Competitive Compensation (base + bonus & equity)
- Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart
- 401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings
- Employee Stock Purchase Plan (ESPP)
- Life and disability insurance
- Generous holiday, vacation, sick and safety leave
- Supportive parental, family care, and military leave programs
- Annual wellness, technology & ergonomic reimbursement programs
- Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering
- Catered lunches + snacks & drinks when working in offices
#LI-REMOTE
#LI-MidSenior
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
$174,900—$242,000 USD
Upstart is a proud Equal Opportunity Employer. We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together.
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 [email protected]
https://www.upstart.com/candidate_privacy_policy
