Staff Applied Scientist

Upstart

. Define technical direction for complex machine learning initiatives, translating broad business objectives into scientific strategies and measurable outcomes .

Posted 11/11/2026full-timeRemote • United States, CanadaLead💰 $199,500 - $276,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining technical direction for machine learning initiatives, leading the design and implementation of advanced modeling approaches, and establishing best practices across teams. Proficient in mentoring and influencing stakeholders while ensuring the quality and scalability of machine learning solutions.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical Evaluation TechniquesTechnical Design and ImplementationDeep Learning KnowledgeMentoring and Influencing Stakeholders

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical MethodsPredictive Performance EvaluationModeling FrameworksEnsemble MethodsProbabilistic ModelingData AnalysisQuantitative Problem SolvingTechnical Architecture DefinitionModel Reliability Assessment

Soft Skills

Technical MentorshipCommunication SkillsInfluencing Technical Direction

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in EngineeringBachelor’s Degree in MathematicsBachelor’s Degree in StatisticsPhD in a Quantitative Field (Preferred)

Industry Keywords

Machine Learning InitiativesModel DevelopmentProduction EnvironmentsLarge-Scale DatasetsScientific Best Practices

About the role

Key responsibilities & impact

Define technical direction for complex machine learning initiatives, translating broad business objectives into scientific strategies and measurable outcomes
Lead the design and evaluation of advanced modeling approaches addressing predictive performance, robustness, and scalability
Identify systemic opportunities to improve model development, experimentation, evaluation, and production performance across teams
Partner with scientific, engineering, and business leaders to influence technical priorities and guide complex modeling tradeoff decisions
Establish scientific best practices, provide technical mentorship, and improve the quality and consistency of machine learning work across the organization

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience
4 years of experience developing machine learning models or applying advanced statistical methods to complex quantitative problems
Experience leading the technical design and implementation of machine learning solutions used in production environments
Experience applying advanced machine learning methods and statistical evaluation techniques to large-scale datasets
Experience defining technical approaches or architecture for machine learning initiatives involving multiple stakeholders or systems
Advanced degree, ideally a PhD, in a quantitative field (preferred)
Knowledge of deep learning, ensemble methods, or probabilistic modeling
Ability to evaluate tradeoffs involving predictive performance, interpretability, scalability, and model reliability
Experience establishing modeling frameworks, evaluation standards, or reusable scientific tools adopted across teams
Skills in influencing technical direction, mentoring scientists, and communicating scientific recommendations to senior stakeholders

Benefits

Comp & perks

Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly
Retirement benefits including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually
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; supplemental health coverage for Canada
Health Savings Account contributions for eligible plans (US only)
Life insurance and disability coverage
Paid time off, sick leave, and company holidays
Paid family and parental leave
Family-centered fertility, parenthood, and caregiving benefits
Employee Assistance Program (EAP) with mental health support and life-centered resources
Financial planning tools and financial concierge service (US only)
Annual wellness allowance
Annual productivity allowance for relevant tools and resources
Team events, all-company updates, and employee resource groups (ERGs)
Catered lunches and stocked micro-kitchens when working from offices in the Bay Area, Austin, Columbus, and New York City