As an Applied Scientist at Upstart, you will develop and evaluate machine learning models that address meaningful business problems. You will collaborate with scientists, engineers, and cross-functional partners to translate complex data into modeling improvements and measurable outcomes.
Locations (5)
Columbus, Ohio, United States
Austin, Texas, United States
Bay Area, California, United States
New York City, New York, United States
Ontario, Canada
Compensation
United States | Remote - Anticipated Base Salary Range
$141,500—$196,000 USD
Canada | Remote - Anticipated Base Salary Range
$130,900—$160,000 CAD
Responsibilities
Develop, train, and evaluate machine learning models to improve predictive performance and support lending decisions.
Analyze large datasets to identify patterns, develop features, and inform modeling approaches.
Design and execute experiments to assess model performance, validate hypotheses, and identify opportunities for improvement.
Collaborate with scientists and engineers to implement, monitor, and refine models in production environments.
Document methodologies, communicate findings, and contribute to reproducible scientific workflows.
Requirements
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
Advanced degree, ideally a PhD, in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field
Lead end‑to‑end AI/ML initiatives, develop and productionize machine learning models, collaborate with product and engineering teams, mentor junior data scientists, and drive complex data science projects from conception to production.
Responsibilities
Lead end‑to‑end AI/ML initiatives
Develop and productionize machine learning models
Collaborate with product and engineering teams
Mentor junior data scientists
Drive complex data science projects from conception to production
Requirements
Graduate degree in Computer Science, Software Engineering, Data Science, Statistics, Mathematics, or equivalent
Nice to have: Generative AI
Nice to have: LLMs
Nice to have: Retrieval‑Augmented Generation (RAG)
Leverage advanced analytics to surface strategic insights and support Questrade’s growth and customer‑centric solutions across a multi‑product, multi‑channel financial services environment.
Compensation
Base salary range: $120,000 - $130,000
The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.
Responsibilities
Supporting Strategy and Corporate Development team with data requests to inform decision making
Collaborating on customer segmentation and profitability analysis
Contributing to set up and inputs for customer / product profitability models
Building and refining predictive models
Identifying opportunities to embed data and analytics throughout strategy and new product development process on an ongoing basis
Lead data science initiatives to derive actionable insights on client experience and journey performance within Scotiabank’s Customer Insights Data and Analytics team.
Compensation
competitive compensation and benefits package
Responsibilities
Develop, test, and implement analytical approaches that uncover meaningful patterns in client behaviour, experience, and journey performance across multiple channels and touchpoints.
Write and maintain high-quality Python and SQL code to source, prepare, and analyze large volumes of structured and unstructured data, building robust analytical datasets and pipelines.
Employ modern NLP techniques—including LLMs, prompt engineering, text classification, topic modelling, sentiment analysis, and information extraction.
Design and apply statistical, machine learning, and exploratory analytical techniques to identify drivers of client satisfaction, friction points in the client journey, and opportunities to improve engagement, retention, and overall experience.
Create compelling data visualizations, dashboards, and reports that clearly communicate insights, trends, and opportunities related to client experience and client journey performance to business and executive stakeholders.
Requirements
University/Post graduate degree in a relevant STEM discipline
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