Applied Artifical Intelligence Sr. Associate

JPMorgan Chase & Co.; Manila; On-site; PHP 5,671,000 - 8,192,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an Applied AI senior associate within Home Lending to turn AI ideas into measurable improvements.

You will partner with product and business teams to test concepts, build prototypes, and scale successful patterns with practical enablement. You will run experiments, develop production-ready prototypes, and help teams adopt AI responsibly by aligning with governance, risk, and control expectations across stakeholders.

Qualifications

• 3 years of experience helping teams integrate emerging technology into business workflows, products, or operations.
• Experience running experiments, pilots, or proofs-of-concept with measurable success criteria.
• Demonstrated experience building prototypes using programming languages commonly used for analytics or machine learning.
• Working knowledge of machine learning concepts and model types used in supervised learning and time series analysis.
• Experience using data analysis techniques to develop insights and communicate recommendations to stakeholders.
• Ability to operate in ambiguity by translating strategy into scoped work, plans, and deliverables.
• Demonstrated experience creating learning content and facilitating workshops for professional audiences.
• Strong communication and stakeholder management skills, including explaining trade-offs, risks, and recommendations.

Responsibilities

• Partner with stakeholders to identify and shape AI opportunities aligned to business outcomes
• Design and run experiments and pilots with clear success metrics (e.g., quality, cycle time, risk reduction, cost, or customer experience)
• Develop prototypes and proof-of-concepts using machine learning and deep learning techniques
• Apply AI methods to problem areas such as speech recognition, natural language processing, and time series forecasting
• Analyze data and produce insights that translate into actionable recommendations and prioritized follow-up work
• Collaborate with engineering and data partners to harden validated prototypes into production-ready solutions when appropriate
• Contribute to a structured intake and prioritization process for business-driven AI ideas, including tracking and stakeholder updates
• Create and deliver enablement materials and workshops to build skills and adoption across teams
• Document patterns, lessons learned, and reusable approaches to help teams apply AI consistently and effectively
• Support responsible AI delivery by aligning solutions to applicable governance, risk, and control expectations
• Maintain data inputs to, and outputs from, relevant databases or analytical systems to support ongoing solution performance

Skills

Experimentation

ML prototyping

Stakeholder comms

Ambiguity handling

Time series analysis

Data-driven insights

Content creation

Cross-team collaboration

Job description

Help teams turn artificial intelligence into practical, measurable improvements. In this role, you will partner across product and business teams to test ideas quickly and scale what works. You will build prototypes that inform production solutions and create enablement that elevates how work gets done. You will also help teams adopt AI responsibly by aligning to appropriate governance and risk expectations. If you enjoy blending hands-on building, experimentation, and influence, this role is for you.

Job summary

As an Applied AI senior associate in Home Lending, you help teams across product and the business get more from AI. You run experiments to identify what improves outcomes, scale successful patterns through enablement and prototypes, and support leaders with practical recommendations on where to focus next. You also help steward responsible adoption by partnering with governance, product, and technology stakeholders.

Job responsibilities

• Partner with stakeholders to identify and shape AI opportunities aligned to business outcomes
• Design and run experiments and pilots with clear success metrics (e.g., quality, cycle time, risk reduction, cost, or customer experience)
• Develop prototypes and proof-of-concepts using machine learning and deep learning techniques
• Apply AI methods to problem areas such as speech recognition, natural language processing, and time series forecasting
• Analyze data and produce insights that translate into actionable recommendations and prioritized follow-up work
• Collaborate with engineering and data partners to harden validated prototypes into production-ready solutions when appropriate
• Contribute to a structured intake and prioritization process for business-driven AI ideas, including tracking and stakeholder updates
• Create and deliver enablement materials and workshops to build skills and adoption across teams
• Document patterns, lessons learned, and reusable approaches to help teams apply AI consistently and effectively
• Support responsible AI delivery by aligning solutions to applicable governance, risk, and control expectations
• Maintain data inputs to, and outputs from, relevant databases or analytical systems to support ongoing solution performance

Required qualifications, capabilities and skills

• 3 years of experience helping teams integrate emerging technology into business workflows, products, or operations
• Demonstrated experience running experiments, pilots, or proofs-of-concept with measurable success criteria
• Demonstrated experience building prototypes using programming languages commonly used for analytics or machine learning
• Working knowledge of machine learning concepts and model types used in supervised learning and time series analysis
• Experience using data analysis techniques to develop insights and communicate recommendations to stakeholders
• Ability to operate in ambiguity by translating strategy into scoped work, plans, and deliverables
• Demonstrated experience creating learning content and facilitating workshops for professional audiences
• Strong communication and stakeholder management skills, including explaining trade-offs, risks, and recommendations

Preferred qualifications, capabilities and skills

• Experience building or scaling enablement, accelerator, or adoption programs across multiple teams
• Experience partnering with governance, risk, controls, or similar stakeholders to support responsible AI delivery
• Experience supporting model evaluation approaches (e.g., test design, quality metrics, monitoring considerations)
• Experience contributing to multiple initiatives in parallel with clear prioritization and delivery discipline
• Evidence of continued learning through delivered projects, publications, or contributions to relevant professional communities