As a Data Scientist within the Auto Finance Data & Analytics team, you will leverage advance analytics and 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. The ideal candidate is a hands-on analytics practitioner who combines strong technical skills, business judgment, intellectual curiosity, and a passion for applying modern analytics and technology to deliver business outcomes.
Job Responsibilities:
- Conduct deep-dive analyses to generate actionable insights and recommendations that streamline business processes and uncover potential areas for product innovation and growth
- Present insights and recommendations to Auto Business leaders using data-driven storytelling to help guide the strategic direction of the organization
- Partner with Business, Product and Technology teams to implement data-driven strategies and models/algorithms that drive business growth and customer engagement
- Develop and apply advanced statistical analyses and mathematical models to analyze complex data trends and patterns
- Leverage AI tools (e.g., LLM Suite, GitHub Copilot, etc.) to work more efficiently, accelerate analysis, and identify opportunities for innovation
- Understand end-to-end digital customer engagement funnel and derive insights on how to improve conversion rates
- Evolve and refine measurement frameworks and KPIs for customer measurement, highlighting anomalies or trends to senior leaders
Required qualification, capabilities and skills:
- 3+ years relevant experience in AI/ML, data science, or related fields.
- Strong background in analyzing and translating digital customer behavior data into actionable insights and recommendations for Business leaders. Experience defining KPIs, measurement frameworks, and anomaly monitoring for digital products.
- Proficient in developing predictive models and utilizing ML algorithms such as logistic regression, KNN, random forest, and Gradient boosting for classification problems.
- Solid understanding of statistical concepts for data analysis and experience with designing and evaluating A/B experiments.
- Experience with Adobe Analytics, Tableau, Alteryx, SQL, Python, and AWS.
- Expertise in prompt engineering and AI-assisted development using LLM Suite, GitHub Copilot Skills, VS Code, etc. to improve LLM output quality and reliability while boosting daily workflow productivity and innovation.
- Experience in building Conversational AI applications and in orchestrating AI/ML services for building a complete solution.
- Demonstrated initiative in learning and applying AI/LLM technologies to business problems and projects.
- Skilled in synthesizing and presenting business insights, recommendations and complex analytical results to executives, business partners, and technical resources across various teams.