Strategic Reporting Senior Associate (Data) - AI Enablement

JPMorganChase; Greater London; On-site; GBP 70,000 - 105,000; Full time

Job summary

JPMorganChase is seeking a Strategic Reporting Senior Associate to blend data, strategy, and delivery, shaping AI-enabled insights that drive decisions and measurable business impact across the firm. You will build scalable data workflows, dashboards, and executive-ready narratives, partnering with stakeholders to translate adoption signals into actionable recommendations.

The role emphasizes collaboration, automation, and reuse of solutions in an AI-first environment, with opportunities to

Qualifications

• Strategic and analytical mindset with ability to challenge the status quo.
• Strong quantitative problem-solving and analytical skills.
• Hands-on Python coding for data wrangling, automation, ETL workflows, and API integrations.
• Working knowledge of Git and modern development practices (branching, pull requests, code review).
• Proficiency with SQL, Tableau, or Alteryx.
• Strong written and verbal communication to create executive-ready materials.
• Ability to manage multiple deliverables and work under time pressure with high attention to detail.
• Ability to influence and align diverse stakeholders.

Responsibilities

• Analyze AI tool adoption and use case data to uncover trends, inefficiencies, and opportunities.
• Translate adoption and portfolio signals into clear narratives, recommendations, and executive-ready materials.
• Develop and maintain intuitive, interactive visualizations and dashboards for senior stakeholders.
• Build production-grade Python data workflows that integrate multiple data sources into cohesive reporting.
• Use Git-based version control and collaborative development practices in shared repositories.
• Design and implement automation to improve data quality, lineage, reproducibility, and near-real-time visibility.
• Identify opportunities for reuse, scalability, standardization, and continuous improvement across reporting processes.
• Contribute to operating model improvements, proof of concepts, and best practices for the AI community.
• Partner across stakeholders to deliver strategic reporting and analytics capabilities from concept through delivery.

Skills

Python

ETL workflows

SQL

Tableau

Alteryx

Git

Data visualization

Executive storytelling

Stakeholder management

Analytical thinking

Tools

Python (data tooling)

Git

Tableau/Alteryx

Job description

Help shape how AI delivers measurable commercial impact across one of the world’s leading financial institutions. In this role, you will turn adoption and portfolio data into clear insights that influence senior leaders and accelerate decision making. You will combine technical execution with stakeholder partnership, building trusted reporting that scales across businesses. You will join a team focused on innovation, reuse of solutions, and an AI-first mindset. If you enjoy connecting data, strategy, and delivery, this is a chance to grow your impact.

As a Strategic Reporting Senior Associate, AI Enablement in the AI Enablement team, you will support centralized reporting, strategic insights, and oversight for AI adoption and the AI and machine learning portfolio. You will track user engagement with AI tools, measure business impact and use case benefits, and analyze tool costs to inform decisions. You will translate complex signals into executive-ready narratives and recommendations. You will also build and maintain scalable data workflows, dashboards, and automation to improve accuracy, visibility, and reproducibility.

Job Responsibilities

• Analyze AI tool adoption and use case data to uncover trends, inefficiencies, and opportunities
• Translate adoption and portfolio signals into clear narratives, recommendations, and executive-ready materials
• Develop and maintain intuitive, interactive visualizations and dashboards for senior stakeholders
• Build and maintain production-grade Python data workflows that integrate multiple data sources into cohesive reporting
• Use Git-based version control and collaborative development practices in shared repositories
• Design and implement automation to improve data quality, lineage, reproducibility, and near-real-time visibility
• Identify opportunities for reuse, scalability, standardization, and continuous improvement across reporting processes
• Contribute to operating model improvements, proof of concepts, and best practices for the AI community
• Partner across stakeholders to deliver strategic reporting and analytics capabilities from concept through delivery

Required Qualifications, Capabilities, and Skills

• Strategic, curious mindset with the confidence to challenge the status quo constructively
• Strong quantitative problem-solving and analytical skills
• Hands-on Python coding capability for data wrangling, automation, ETL-style workflows, and API integrations
• Working knowledge of version control using Git and modern development practices (branching, pull requests, code review)
• Proficiency with analytics and visualization tools such as SQL, Tableau, or Alteryx
• Strong written and verbal communication skills, including ability to create executive-ready materials
• Ability to manage multiple deliverables, prioritize effectively, and deliver under time pressure with high attention to detail
• Ability to influence and drive alignment across a diverse set of stakeholders

Preferred Qualifications, Capabilities, and Skills

• Knowledge of data engineering concepts such as data modeling, ETL and ELT patterns, data validation, monitoring, and performance considerations
• Experience designing or partnering on UI and UX for dashboards and internal reporting experiences
• Experience improving reporting operating models through standardization, reuse, and scalable delivery practices

JPMorganChase’s AI Enablement team drives adoption of AI and accelerates the analytics agenda globally across Markets, Payments, Securities Services, and Global Banking by integrating AI into business workflows and scaling solutions for measurable impact.

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