Research Scientist - ML Fairness & Explainability

Upstart; United States; Remote; USD 126,000 - 175,000; Full time

Job summary

A leading AI lending marketplace is seeking a ML Research Scientist to ensure fair lending compliance. You will research and implement methodologies for evaluating the fairness of machine learning models within a remote working environment. The role requires strong academic credentials, proficiency in Python, and a passion for the mission of enabling access to affordable credit. Competitive compensation and comprehensive benefits are offered.

Benefits

Competitive Compensation (base + bonus & equity)

Comprehensive medical, dental, and vision coverage

401(k) with company match

Employee Stock Purchase Plan (ESPP)

Generous holiday, vacation, and sick leave

Catered lunches in offices

Qualifications

• Strong academic credentials with a master's degree in relevant fields.
• Experience with ML explainability or fairness.
• Full-stack expertise from ideation to productionalizing code.

Responsibilities

• Ensure fair lending compliance and evaluate fairness of ML models.
• Research and implement methodologies for explaining complex ML models.
• Proactively communicate technical results to stakeholders.

Skills

Programming skills in Python

Statistical and machine learning concepts

Strong problem-solving skills

Proactive communication

Intellectual curiosity

Education

Master's degree in quantitative areas

Ph.D. preferred

Job description

About Upstart

Upstart is the 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 delivering the digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload.

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’s Machine Learning team has a direct impact on our company's success. The team consists of Research Scientists, Data Scientists, ML Engineers and other highly specialized roles. The team builds, enables and evaluates our core production models.

Because our challenges are new, members of our Machine Learning team need strong creative problem-solving skills and the technical background to implement solutions. The research environment affords team members the opportunity to utilize a variety of statistical and machine learning methods with the freedom and encouragement to pursue alternative approaches to solving problems. Whether developing new products or identifying novel approaches to core models, we are continuously seeking the next big ideas to move our business forward.

The role sits on the Fairness and Explainability team. The team is focused on research and development ensuring our models are both fair and explainable. This function is essential for Upstart to ensure that our models are compliant, robust, and are able to engender trust with a variety of external stakeholders, including lending partners, investors, and consumers.

The Role

As a ML Research Scientist, you will be an integral part of the team ensuring fair lending compliance. You\'ll enjoy a fast-paced environment with a focus on researching and implementing industry leading methodologies for explaining complex machine learning models, evaluating their fairness in the lending space, and mitigating any potential fairness disparities via less discriminatory alternative searches. You will strive to understand, at a deep level, the dynamics of our models in order to properly inform business decisions.

What we’re looking for

• Strong academic credentials with a master's degree in statistics, mathematics, economics, physics, operations research, computer science, or other quantitative areas of study; Ph.D. preferred
• Programming skills in Python
• Full-stack expertise with all steps of the modeling process from ideation to productionalizing code; OR deep expertise in either statistical modeling or machine learning
• Experience and interest in ML explainability or fairness; OR demonstration of high potential to learn quickly and contribute to these areas.
• Proficiency in a broad array of mathematical, statistical learning and machine learning concepts and applications
• Detailed understanding of building good technical solutions; ability to convert ideas into testable hypotheses and/or next steps
• Ability to meet team standards with respect to quality and velocity with minimal help or direction from peers
• For more complex tasks, ability to break down problems into smaller tasks, and use them to estimate the timeline of executing a larger initiative. Willingness to make the right tradeoffs when needed to deliver projects on time.
• Proactively communicate to stakeholders and teammates with ability to contextualize technical results
• Strong sense of intellectual curiosity balanced with humility, drive and teamwork
• Numerically-savvy and smart with ability to operate at a speedy pace
• Enthusiasm for and alignment with Upstart’s mission and values

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 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-Associate

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 $126,400 — $175,000 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 [e-mail]

https://www.upstart.com/candidate_privacy_policy