Applied AI ML Lead, AI Data Readiness
Software Engineering, Data Science
You will shape how data becomes usable for conversational analytics and AI-assisted experiences across the organization. You will define practical standards and patterns that make data easier to discover, interpret, and use safely at scale. You will collaborate with data product owners and engineering teams to deliver prototypes and production-ready capabilities. You will demonstrate progress through measurable scorecards and clear executive updates.
As an Applied AI ML , Lead - AI Data Readiness at JPMorganChase within Corporate & Investment Bank Data Strategy, you will define and deliver the data foundations that enable conversational analytics and agentic access to data at scale. You will set standards for semantic and contextual consistency, improve metadata and data quality practices, and guide teams toward measurable improvements in AI-readiness. You will translate complex technical gaps into clear roadmaps and demonstrate incremental business value through frequent prototypes and executive-ready updates.
Job responsibilities
- Define and implement an enterprise AI data readiness framework that enables reliable agentic consumption of data products
- Establish standards for semantic and context layers to improve consistency, interpretability, and reuse across analytics experiences
- Design and deliver metadata, lineage, and data quality practices that improve discoverability and reduce ambiguity in AI-driven analysis
- Build and iterate proof-of-concept and production-ready prototypes for conversational analytics use cases
- Improve performance and reliability of natural-language-to-database-query systems by analyzing failures and driving targeted remediation
- Identify semantic and contextual gaps that prevent accurate AI-driven data access, and partner with owners to close them
- Partner with data product leaders and engineers to prioritize and execute quality and usability improvements across critical datasets
- Define scalable AI interface patterns for copilots, agents, and analytics tools to ensure consistent user outcomes
- Create scorecards, key performance indicators, and maturity models that track progress and drive accountability
- Deliver regular demonstrations and executive updates that connect technical improvements to business impact
Required qualifications, capabilities and skills
- Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience
- Experience designing or operating agentic querying approaches, including semantic and context layers and query agents (for example, Databricks Genie, Snowflake Cortex Analyst, or similar)
- Proven expertise in metadata management and data catalog ecosystems, including improving discoverability and interpretability
- Hands-on experience with conversational analytics and natural-language querying systems, including an understanding of common failure modes
- Ability to prototype and build solutions across the data and application stack to accelerate learning and delivery
- Experience working with enterprise data platforms and data products, including stakeholder-driven prioritization
- Strong analytical problem-solving skills, with the ability to diagnose root causes and drive durable remediation
- Demonstrated success partnering across product, engineering, and business teams in complex, regulated environments
- Strong executive communication and storytelling skills, including delivering clear updates and influencing roadmaps
- Ability to operate effectively in a fast-paced, iterative delivery model with measurable outcomes
Preferred qualifications, capabilities and skills
- Experience in financial services or other large-scale enterprise environments
- Experience bridging data product management and artificial intelligence solution delivery
- Full-stack engineering experience to support rapid prototyping and experimentation
- Experience building or governing semantic models and metrics layers for enterprise analytics at scale
#LI-RB3
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Build AI-ready data foundations to enable scalable conversational analytics and agentic access to data.