Applied Scientist

Summary

Upstart is an AI lending marketplace that uses advanced technology to expand access to affordable credit. The Applied Scientist will improve and develop machine learning models for borrower acquisition across marketing channels, conduct causal analysis and experimentation, and build production-ready data and modeling solutions in partnership with Machine Learning, Growth, and Marketing Platform Engineering teams.

Responsibilities

• Analyze historical model and campaign performance to identify opportunities to improve model effectiveness and marketing outcomes
• Develop and evaluate machine learning models, including researching new features and model architectures, to improve prospect selection and support new marketing use cases
• Design statistically rigorous experiments and model evaluations to measure causal impact, optimize campaign outcomes, and inform decisions
• Navigate complex, messy datasets and build reusable data pipelines, metrics, and analytical approaches that enable efficient model development and analysis
• Partner with Machine Learning, Growth, and Marketing Platform Engineering teams to translate business problems into research agendas, intermediate milestones, and production-ready solutions
• Expand machine learning capabilities beyond direct mail into lifecycle, email, digital, and other emerging marketing channels

Skills

• Master's Degree in Mathematics, Statistics, Economics, Operations Research or a related field
• Experience applying statistical and machine learning methods to modeling or data science problems
• Experience using Python for data analysis, data preparation, and machine learning model development
• Experience with causal inference and experimental design, including statistically rigorous evaluation of model or experiment performance
• 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
• PhD in Mathematics, Statistics, Economics, Operations Research or a related field (or its equivalent)
• Knowledge of causal machine learning methods and modeling approaches
• Ability to translate broadly scoped business problems into structured research questions, analyses, and modeling approaches
• Experience working across exploratory data analysis, machine learning research, experimentation, and production model development and scaling
• Ability to interpret complex experimental or modeling results and translate findings into actionable recommendations
• Experience applying machine learning to marketing, customer acquisition, lifecycle, or other growth use cases

Qualifications

Must Haves

• Master's Degree in Mathematics, Statistics, Economics, Operations Research or a related field
• Experience applying statistical and machine learning methods to modeling or data science problems
• Experience using Python for data analysis, data preparation, and machine learning model development
• Experience with causal inference and experimental design, including statistically rigorous evaluation of model or experiment performance
• 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

Nice to Haves

• PhD in Mathematics, Statistics, Economics, Operations Research or a related field (or its equivalent)
• Knowledge of causal machine learning methods and modeling approaches
• Ability to translate broadly scoped business problems into structured research questions, analyses, and modeling approaches
• Experience working across exploratory data analysis, machine learning research, experimentation, and production model development and scaling
• Ability to interpret complex experimental or modeling results and translate findings into actionable recommendations
• Experience applying machine learning to marketing, customer acquisition, lifecycle, or other growth use cases

Benefits

• Target bonus opportunities
• Annual equity grants that vest quarterly
• 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, including medical, dental, vision, and wellness resources for US employees and supplemental health coverage for Canada
• Health Savings Account contributions from Upstart for eligible plans (US only)
• Life insurance and disability coverage
• 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 planning tools and a financial concierge service (US Only)
• Annual wellness allowance to support physical and emotional well-being and personal development
• Annual productivity allowance to invest in relevant tools and resources
• 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!)
• 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)
• Regular onsites and in-person meetings for collaboration
• Team onsites, planning sessions, and moments that spark creativity and trust
• Support to work primarily from home or collaborate in-person from one of our offices