About the role
from listingUse machine learning and advanced analytics to improve Auto Finance digital experiences and drive growth decisions.
Build products that help customers move forward with confidence in one of life’s biggest purchases. In this role, you’ll turn digital behavior and performance data into insights that shape strategy and improve conversion across the customer journey. You’ll work side-by-side with Product, Technology, Design, and Risk partners to deliver measurable outcomes. If you enjoy owning analyses end-to-end and applying modern machine learning to real customer problems, you’ll thrive here.
Job Summary
As a Data Scientist within the Auto Finance Data & Analytics team, you will leverage advanced analytics and artificial intelligence and machine learning (AI/ML) to support product teams, build analytical solutions, guide strategic business decisions, and enable growth initiatives. You will partner closely with Product, Technology, Design, Risk, and other cross-functional teams to translate complex business questions into analytical and AI/ML solutions.
You will combine hands-on technical execution with business judgment and clear, data-driven storytelling. You will help establish and evolve the measurement frameworks that keep leaders informed and teams accountable.
Job Responsibilities
Conduct deep-dive analyses to generate actionable insights and recommendations that streamline processes and uncover opportunities for product innovation and growth.
Present insights and recommendations to business leaders using clear, data-driven storytelling to help guide strategic direction.
Partner with Business, Product, and Technology teams to implement data-driven strategies and models that drive growth and customer engagement.
Develop and apply statistical analyses and mathematical models to identify trends and patterns in complex data.
Leverage firm-approved AI tools (for example, LLM Suite and GitHub Copilot) to accelerate analysis and identify opportunities for innovation.
Analyze the end-to-end digital customer engagement funnel and recommend improvements to increase conversion.
Evolve and refine measurement frameworks and key performance indicators, highlighting anomalies and trends to senior leaders.
Required Qualifications, Capabilities, and Skills
Three years of relevant experience in data science, machine learning, or a related field.
Demonstrated experience translating digital customer behavior data into actionable insights and recommendations for business leaders.
Demonstrated experience defining key performance indicators, building measurement frameworks, and monitoring for anomalies in digital product performance.
Proficiency developing predictive models and applying classification algorithms (for example, logistic regression, k-nearest neighbors, random forest, and gradient boosting).
Solid understanding of statistical concepts for data analysis and experience designing and evaluating A/B experiments.
Hands-on experience with SQL and Python for data extraction, analysis, and model development.
Experience using analytics and visualization tools such as Adobe Analytics and Tableau (or equivalent tools).
Strong ability to synthesize complex analytical results and communicate recommendations to executive, business, and technical stakeholders.
Preferred Qualifications, Capabilities, and Skills
Experience building conversational artificial intelligence solutions and orchestrating machine learning services into an end-to-end application.
Amazon Web Services (AWS) Certified Cloud Practitioner certification.