Lead Solutions Analyst-Data Analyst

JPMorganChase; Houston (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

JPMorganChase is seeking a Lead Solutions Analyst in Houston to bridge business needs with product, platform and development teams within Corporate Technology.

You will translate complex requirements into feasible, well-documented solutions for Know Your Customer and risk initiatives, using AI-assisted analysis with strong validation and data governance practices.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Extensive experience of data analysis, data mapping and working with large data sets.
• Proven ability to work across business streams and have exposure to front to back system implementation.
• Strong understanding of key technology concepts, business and technical architecture.
• Ability to translate and document business needs into functional requirements and produce quality documentation.
• Ability to drive multiple agendas and effectively manage priorities.
• Pragmatic team player with an attention to detail.
• Experience using enterprise AI capabilities to support analyses and validate results.
• Ability to review and validate AI-assisted analyses and recommendations.

Responsibilities

• Review business requirements and ensure the complete scope of business needs is articulated.
• Perform detailed analysis on requirements and develop standard, reusable solutions.
• Build functional solutions for ongoing KYC and Risk Assessment initiatives.
• Prepare detailed interface mapping documents and static data.
• Review solutions and interface mappings with business and tech stakeholders to ensure alignment with customer expectations and business needs.
• Ensure overall quality of functional solutions and interface mappings across the program.
• Assist the business with onboarding UAT, including test cases, planning, and tracking.
• Collaborate with BAs and team members to evenly distribute work and meet targets.
• Engage with business and technology stakeholders to strengthen relationships.
• Identify risks early and communicate mitigation steps to stakeholders.
• Promote reuse-first and AI-assisted practices with strong data sensitivity awareness.

Skills

Data analysis

Data mapping

Business analysis

AI in analytics

Requirements documentation

Stakeholder management

Job description

Description

Job Description

As a Lead Solutions Analyst at JPMorganChase within the Corporate Technology, you review business requirements and ensure that the complete scope of business needs is articulated. Your deep understanding of applications, platforms, and products will position you as a key bridge between product owners, business, operations, and software developers. Utilizing advanced analytical reasoning and technical fluency, you will translate complex business requirements into well-structured and technically feasible solutions. You will make data-informed decisions and provide strategic insights to support key business initiatives. As a Lead Solutions analyst, you\'ll navigate ambiguity, manage change effectively, and communicate compellingly with diverse stakeholder audiences to ensure the highest quality and professionalism in service delivery.

Job responsibilities :

• Review business requirements and make sure that requirements are captured are articulating the complete scope of business needs.
• Perform detailed analysis on the requirements and come up with standard and re-usable solutions.
• Build functional solutions which meets business requirements of ongoing KYC and Risk Assessment initiatives.
• Prepare detailed interface mapping documents and static data that meets all the solutions and business requirements.
• Review the solutions and interface mapping documents with business and technology stake holders to make sure that they are aligned with customer expectations and business needs.
• Ensure the overall quality of functional solutions, interface mapping documents are in-line with standard practices we follow across the program in the bank.
• Assist the business with the onboarding UAT, including test cases preparation, planning, communication, and close tracking of activities.
• Work proactively with fellow BAs and other team members, ensuring work is proportionally distributed and targets are met.
• Proactively engage, manage and build strong relationships with both business and technology stakeholders.
• Identify risks and issues early, plan mitigating steps and communicate these to business stakeholders in a timely manner.
• Promotes reuse-first, AI-assisted practices for analysis and documentation across the team, ensuring human review and alignment to delivery standards.

Required qualifications, capabilities and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Extensive experience of data analysis, data mapping and working with large data sets.
• Proven ability to work across business streams and have exposure to front to back system implementation.
• Strong understanding of key technology concepts, business and technical architecture.
• Ability to accurately translate and document business needs into functional requirements and produce quality documentation.
• Ability to drive multiple agendas and effectively manage priorities.
• Ability to work proactively, independently and displays strong initiative.
• Pragmatic team player with an attention to detail.
• Demonstrable experience using enterprise-authorized AI capabilities within the work environment to support solutions analysis workflows with strong validation habits and awareness of data sensitivity
• Ability to review and validate AI-assisted analyses and recommendations before use, escalating when uncertain and following data handling expectations

Preferred qualifications, capabilities, and skills

• Experience working on Know Your Customer, Anti-Money Laundering, or broader risk and compliance technology program.
• Familiarity with agile delivery methodologies and experience working within cross-functional product teams.
• Exposure to data governance frameworks and enterprise data management practices.