Data Scientist - Applied AI/ML

JPMorganChase; Taguig; Hybrid; PHP 900,000 - 2,000,000; Full time

Job summary

JPMorganChase in Metro Manila invites a Senior Associate to shape data science, ML, and Generative AI across Shared Services. You will design, deploy, and operate predictive models and agentic workflows that improve risk assessment, governance reporting, and change mapping.

You will partner with product, engineering, and risk stakeholders, drive measurable outcomes, and ensure responsible AI practices across the lifecycle of models and tools.

Qualifications

• Bachelor’s degree in data science, computer science, statistics, mathematics, or a related field
• Three years of experience delivering end-to-end AI or ML solutions to production
• Strong Python proficiency for data analysis, modeling, and production implementation
• Experience building, evaluating, and deploying predictive models using common libraries
• Experience building and deploying large language model workflows with RAG and tool/call integration
• Experience defining evaluation approaches for large language model solutions
• Experience operating production pipelines with versioning, CD, monitoring, and incident hygiene
• Knowledge of cloud and containerized environments (AWS, Azure, GCP, Kubernetes)
• Strong communication skills to translate business problems into technical outcomes

Responsibilities

• Design, develop, and deploy predictive ML and analytics solutions
• Build and integrate agentic workflows into end-to-end business processes
• Prototype AI approaches and productionize successful prototypes
• Own end-to-end model delivery from data prep to deployment
• Design, deploy, and operate production pipelines with monitoring and cost improvements
• Partner with product, engineering, risk, and controls stakeholders
• Apply responsible AI and governance practices across model lifecycle
• Contribute reusable patterns and libraries across teams

Skills

Python

End-to-end ML delivery

Communication

Risk & controls

Governance & ethics

Education

Bachelor’s in data science / CS / statistics / math

Master’s degree preferred

Tools

PyTorch

TensorFlow

Scikit-learn

RAG workflows

Cloud platforms

Kubernetes

Job description

Join a world-class Applied AI/ML organization at JPMorganChase and help shape how teams across the firm use data science, machine learning, and Generative AI to solve real business problems.

As a Senior Associate in Applied Artificial Intelligence and Machine Learning within Shared Services, you design and deploy predictive models, advanced analytics, and large language model agentic solutions that orchestrate tools and workflows inside business processes. You will build reusable services that teams can adopt to improve risk assessment support, legal and regulatory change mapping, control design and testing, sustainable monitoring, issue tracking, and governance reporting.

Job Responsibilities

• Design, develop, and deploy predictive machine learning, advanced analytics, and generative AI solutions for complex business problems
• Build and integrate agentic workflows into end-to-end business processes, including retrieval-augmented generation, tool or function calling, routing, and structured outputs
• Prototype AI-enabled approaches quickly and harden successful prototypes into reusable, production-ready services with measurable outcomes
• Own end-to-end model delivery, including dataset preparation, feature engineering, training, validation, evaluation, deployment, and iteration
• Design, deploy, and operate production pipelines and services (batch and real-time), including monitoring, retraining strategies, and reliability and cost improvements
• Partner with product, engineering, and risk and controls stakeholders to define requirements, align on success metrics, and drive adoption
• Apply responsible AI and governance-aligned practices across the model and agent lifecycle, including evaluation, guardrails, and documentation
• Contribute reusable patterns, templates, and libraries that accelerate delivery across teams

Required qualifications, capabilities, and skills

• Bachelor’s degree in data science, computer science, statistics, mathematics, or a related technical field (or equivalent practical experience)
• Three years of experience delivering end-to-end AI or machine learning solutions from prototype to production (or production-like) deployment
• Strong Python proficiency for data analysis, modeling, and production implementation
• Experience building, evaluating, and deploying predictive models (for example, classification, regression, or natural language processing) using common libraries (for example, PyTorch, TensorFlow, or scikit-learn)
• Experience building and deploying large language model workflows that include retrieval-augmented generation and tool or function calling
• Experience defining and using an evaluation approach for large language model solutions (for example, test sets, regression tests, or structured human review)
• Experience operating production pipelines or services, including versioning, continuous delivery practices, monitoring and alerting, and incident hygiene
• Working knowledge of cloud and or containerized environments (for example, Amazon Web Services, Microsoft Azure, Google Cloud Platform, or Kubernetes)
• Strong communication skills, including the ability to translate business problems into measurable technical outcomes and explain results to diverse audiences

Preferred qualifications, capabilities, and skills

• Master’s degree or doctorate in a quantitative field
• Publications, patents, or meaningful open-source contributions related to machine learning or generative AI
• Experience scaling agentic systems across multiple use cases, including mature evaluation practices and quality dashboards
• Experience implementing guardrail patterns and operating controls for generative AI features in production
• Experience with large-scale data processing and cloud data services, and exposure to performance optimization for model serving
• Experience in financial services or other regulated industries, including comfort operating within governance and change management expectations
• Experience with specialized domains such as search and ranking, recommender systems, graph machine learning, or knowledge graphs