Data Scientist Senior Associate

JPMorgan Chase · Banking · Plano, TX +1 · Consumer & Community Banking

Data Scientist Senior Associate at JPMorgan Chase within the Auto Finance Data & Analytics team, focusing on leveraging AI/ML for product teams, building analytical solutions, and guiding strategic business decisions. The role involves deep-dive analyses, presenting insights, implementing data-driven strategies, developing statistical models, and utilizing AI tools for efficiency and innovation. Requires experience in predictive modeling, ML algorithms, A/B testing, prompt engineering, conversational AI applications, and orchestrating AI/ML services.

What you'd actually do

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

Skills

Required

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.

What the JD emphasized

AI/ML
Conversational AI applications
orchestrating AI/ML services
prompt engineering
AI-assisted development

Other signals

Leverage AI tools (e.g., LLM Suite, GitHub Copilot, etc.) to work more efficiently
Experience in building Conversational AI applications and in orchestrating AI/ML services for building a complete solution.
Expertise in prompt engineering and AI-assisted development using LLM Suite, GitHub Copilot Skills, VS Code, etc.

Read full job description

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.

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.