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 wil 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 About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the TeamOur Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Bring your expertise to a Home Lending Data and Analytics team that partners with sales leaders to solve complex business problems. You’ll deliver actionable insights that improve strategy, performance, and customer outcomes. You’ll combine strong data skills with business context to drive measurable impact. You’ll work in a fast-paced, matrixed environment with close stakeholder partnership and clear ownership of outcomes. If you enjoy turning data into decisions, this role is for you. Job summary As a Quantitative Analytics Senior Associate in Home Lending Data and Analytics supporting Sales, you deliver advanced analytics that informs sales strategy and optimization. You combine data manipulation, quantitative analysis, and business judgment to identify opportunities and recommend actions. You build clear reporting and compelling narratives that help stakeholders make decisions with confidence. You explore opportunities to apply automation and artificial intelligence to improve analytics workflows and business outcomes. Job responsibilities - Deliver advanced analytics and data-driven solutions for a wide range of home lending sales business challenges - Explore, assemble, organize, and analyze data using internal and external data sources and tools - Perform descriptive, diagnostic, and predictive analyses to uncover trends, patterns, and actionable insights - Create clear visualizations and narratives that communicate insights and recommendations to business stakeholders - Identify opportunities to enhance business intelligence and automate reporting to support decision-making - Build analytical frameworks that support strategic and complex business priorities - Collaborate with business and technology partners to strengthen data foundations and apply artificial intelligence to automate and deliver innovative solutions Required qualifications, capabilities, and skills - Bachelor’s or advanced degree in an analytical field (for example, computer science, economics, mathematics, statistics, engineering, or operations research) - Two years of experience in data analysis or data science - Proficiency with SQL for data extraction, transformation, and validation - Proficiency with Python for analysis and automation - Proficiency with Microsoft Excel for analysis and reporting - Experience using data visualization tools to communicate insights - Strong critical thinking skills, including the ability to connect analysis to business strategy and measurable outcomes - Strong written and verbal communication skills, including data storytelling for business stakeholders Preferred qualifications, capabilities, and skills - Experience using cloud platforms for large-scale data processing (for example, Amazon Web Services or Snowflake) - Experience with Salesforce for lead management and sales workflows - Experience using GitHub for collaborative analytics and version control - Strong experience with visualization tools, including products with artificial intelligence and natural-language capabilities - Experience in financial services, including mortgage business experience About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the TeamOur Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Bring your expertise to a Home Lending Data and Analytics team that partners closely with product, marketing, and sales to solve complex problems. You will work in a fast-paced, matrixed environment where rigorous analysis and practical recommendations promote measurable outcomes. You will help improve customer experience by identifying opportunities, clarifying trade-offs, and informing decisions with data. If you enjoy hands-on analytics with real business impact, this role is for you. Job summary As a Senior Associate Data Scientist in Home Lending Data and Analytics supporting the Originations Product team, you translate data into clear insights and recommendations that guide product decisions and business outcomes. You define success metrics, validate data, and deliver measurement that stakeholders can trust. You partner with analytics and predictive modeling teams to enable reliable analysis and model development through strong data identification and quality checks. You communicate findings effectively to technical and non-technical audiences so decisions are timely and well-supported. Job Posting Standards and Components.pdf Job responsibilities - Identify and quantify obstacles to business goals using analytics and data science techniques - Analyze data to uncover trends, drivers, and patterns and translate findings into clear narratives that inform decisions - Define success metrics and measurement approaches that align to product goals and stakeholder needs - Validate data sources and perform data quality checks to enable reliable analysis and model development - Extract, transform, and analyze data from multiple sources using SQL to produce reproducible datasets - Partner cross-functionally to identify friction points and opportunities and recommend practical improvements - Surface data-driven opportunities to improve efficiency, reduce friction, and enhance customer experience - Gather requirements, clarify business questions, and align stakeholders on analytical approach and deliverables - Deliver timely analyses and summaries tailored to the audience and decision context - Document work, share best practices, and contribute to team standards for rigor, quality, and learning - Maintain strong attention to detail and analytic integrity in a fast-paced environment Job Posting Standards and Components.pdf Required qualifications, capabilities, and skills - Three years of experience in analytics, data science, business intelligence, or a related quantitative role - Strong SQL skills, including complex querying, joins, aggregations, and data validation - Proficiency in at least one of the following: Python, SAS, or R - Demonstrated ability to translate analysis into actionable insights and recommendations - Strong written and verbal communication skills for technical and non-technical audiences - Strong analytical and critical thinking skills, with the ability to connect detail to business context - Ability to manage multiple priorities, work independently, and deliver high-quality work under time constraints - Strong interpersonal skills and experience collaborating across teams and functions Job Posting Standards and Components.pdf Job Posting Standards and Components.pdf Preferred qualifications, capabilities, and skills - Experience in mortgage banking or financial services - Experience in stakeholder-facing analytics, consulting, or strategy work in ambiguous problem spaces - Experience supporting change initiatives or operational and process improvements through analytics - Experience designing, supporting, or evaluating tests or experiments using basic statistical concepts - Demonstrated interest in continuous learning and adopting new analytical approaches, tools, or methods Preferred Background - Experience in Mortgage Banking or Financial Services is preferred but not required. - Exposure to consulting, strategy, or stakeholder-facing analytics work is a plus, particularly where requirements are ambiguous and problems are not well-defined. - Experience supporting change initiatives or operational/process improvements through analytics is beneficial. - Demonstrated interest in continuous learning and adopting new analytical approaches, tools, or methods to improve outcomes. - Experience designing, supporting, or evaluating tests or experiments using basic statistical concepts. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the Team Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

Role Description We are seeking an experienced Senior Data Scientist to join our growing Healthcare domain team. As a key contributor, the Senior Data Scientist will be responsible for leveraging their advanced data analysis and machine learning skills to solve complex healthcare challenges, ultimately driving data-driven decision-making to positively impact patient outcomes and clinical workflows. - Model Research & Development: Conduct independent and collaborative research and development of data science and machine learning models; develop cutting-edge models that drive clinical and business value, leveraging health records, clinical trials, and other healthcare data sources. - Continuous Capability Growth: Maintain and improve your knowledge of decision science, communicating data, domain modeling, predictive modeling, advanced analytics, MLOps, Research, and Healthcare/AI Ethics, with the willingness to upskill others in these competencies. - Collaborate Cross-Functionally: Work closely with cross-functional teams (including clinical experts, product managers, and software engineers) to apply data science models to complex healthcare problems, ensuring that models are integrated into production products and services. - Communicate Results & Impact: Communicate technical results and clinical impacts to stakeholders, including medical professionals, administrative leaders, and technical audiences. - Stay Current with Industry Developments: Keep up to date with developments across data science, machine learning, and public health/clinical health studies, identifying opportunities for applied research and development. - Mentor Junior Talent: Mentor junior data scientists within the domain, fostering a culture of continuous improvement, scientific rigor, and innovation. Qualifications - 5+ years of experience in data science and machine learning, with a strong track record of independent research and development. - Demonstrated expertise in the Healthcare industry (e.g., clinical data, healthcare operations, patient outcomes, HIPAA compliance, or bioinformatics). - Fluency in Python with experience with at least one cloud provider; preferably Azure. - Qualified experience in a related field, including, but not limited to, Data Science, Machine Learning, Computer Science, or Statistics. M.Sc preferred. - Strong experience in delivery across the lifecycle of machine learning products, adhering to robust software engineering practices and data governance/privacy standards. - Excellent communication and collaboration skills, with the ability to build trust and work effectively alongside clinical and technical cross-functional teams. - Pan-African Remote: You live anywhere on the African continent and have a reliable setup for working remotely. How we work Due to the highly collaborative and internationally distributed nature of our work, successful candidates must be comfortable operating in small teams while contributing to larger, globally coordinated efforts. A strong sense of ownership, self-motivation and discipline in maintaining clear and consistent communication through virtual collaboration tools and video conferencing is essential.