Chase (J.P. Morgan) is hiring a Lead/Senior Data Analyst for its Platform Team in London. Own the data-as-a-product strategy using dbt, BigQuery, Looker, and Python.

About the Company: Global Financial Leadership & Digital Disruption

J.P. Morgan is a global leader in financial services, providing strategic advice, capital, and innovative products to the world’s most prominent corporations, governments, institutional investors, and retail consumers. Operating under the principle of doing “first-class business in a first-class way,” the firm builds trusted, long-term partnerships designed to drive economic progress and infrastructure stability worldwide.

Following the highly successful 2021 launch of Chase in the UK—the firm’s innovative, mobile-first digital banking arm—a dynamic platform ecosystem has evolved within the Corporate Sector. This digital banking venture operates with the agility of a fintech scale-up while leveraging the deep capital, security architecture, and regulatory backing of J.P. Morgan. Built on a people-first culture that values curiosity, collaboration, and high commitment, this division designs advanced cloud-native products that place customers at the absolute center of the banking experience.

About the Role: Lead / Senior Data Analyst (Platform Data Discipline)

Are you an expert data strategist who wants to step out of reactive reporting and explicitly shape a brand-new data culture? The Chase Platform Team is accepting applications for a Lead / Senior Data Analyst at its milestone corporate headquarters in Canary Wharf, London.

As the foundational Senior Analyst in this space, you will take complete ownership of our data-as-a-product strategyfrom conception to deployment. This is a unique, highly visible role where you will establish what exceptional data analysis looks like for our platform infrastructure. You will partner directly with product management, core engineering, operations, and executive leadership to translate complex system behaviors into actionable business outcomes. If you are a hands-on, detail-oriented professional who loves clearing backlogs, automating pipelines, and leveraging data storytelling to influence major product decisions, this role offers the perfect sandbox for innovation.

Key Responsibilities & Analytics Workflows

• Establish the Data Discipline: Define, implement, and manage the core data analysis standards, frameworks, and best practices across the platform department.

• Own the Data Product Strategy: Maintain the data analysis backlog, transforming raw business problems and customer needs into functional data features.

• Deliver High-Impact Intelligence: Write advanced SQL queries and build clean, insightful dashboards and metrics reports for senior stakeholders and executive leadership.

• Optimize & Scale Operations: Automate legacy reporting pipelines and scale data operations using modern workflow orchestrators and data transformation tools.

• Hypothesis Validation & Modeling: Develop, run, and validate quantitative hypotheses using A/B testing frameworks, statistical regression, and predictive forecasting models.

• Data Governance & Controls: Oversee data quality, establishing robust data governance compliance parameters and pipeline controls across diverse, large-scale datasets.

This role requires a balanced mix of deep technical execution, statistical rigour, and the communication skills necessary to advocate for a data-driven engineering culture.

Required Technical & Professional Expertise:

• Advanced Analytics Stack: Direct proficiency using dbt (data build tool), BigQuery (or equivalent cloud data warehouses), and Looker Studio Pro.

• Data Pipeline Orchestration: Practical exposure to workflow automation engines like Apache Airflow or similar platforms.

• Programming & Manipulation: Strong Python coding skills specifically geared toward data modelling and manipulation using pandas, polars, numpy, or similar libraries.

• Query Mastery: Exceptional, advanced SQL skills for isolating and pulling complex, multi-source datasets.

• Statistical Foundation: Hands-on experience executing regression models, hypothesis validation, A/B testing, and predictive analytics.

• Data Architecture Governance: Clear understanding of data quality controls, compliance management, and corporate data governance.

• Stakeholder Management: Exceptional communication skills with a proven track record of translating technical data architecture findings into simple narratives for non-technical stakeholders.

Preferred Qualifications & Strategic Assets:

• A university degree in a highly quantitative discipline (such as Mathematics, Statistics, Computer Science, Economics, or an equivalent field).

• Direct experience working with cloud-native platform infrastructure ecosystems (GCP or AWS).

• Prior analytical experience operating within the financial services or digital banking sectors.

• A fundamental understanding of machine learning principles and predictive model architectures.

Key Job Details

• Job Identification: 210696379

• Job Category: Analytics Solutions & Delivery

• Primary Location: 1 Cabot Square, London, E14 4QJ, United Kingdom

• Schedule & Classification: Full-Time corporate schedule