JC
JPMorgan Chase
Data Analyst

Quant Analytics Associate -Digital

On-siteMidData Analystposted 2w ago
✦Role summaryAI-generated

The Quant Analytics Associate will lead the design and execution of A/B experiments and KPI governance to drive digital product performance for JPMorgan Chase’s Consumer & Community Banking division. By translating advanced analytics into actionable insights, the role will shape product roadmaps and support a hyper‑personalized, data‑driven customer experience across multiple channels.

Skills required

About this role

We have an exciting opportunity for you to enhance your career by joining Consumer & Community Banking - Data & Analytics team

As a Quant Analytics Associate on the Digital Analytics team, you will support an extensive portfolio of digital products by leveraging advanced analytics to enhance customer experience, optimize product performance, and strengthen long-term, profitable customer relationships. In this role, you will contribute towards high-impact analytics book of work that enables Chase’s cross-channel, cross-line of business strategy to evolve toward a hyper-personalized, data-driven, customer-centric model.


You will bring analytics thought process to define and govern KPIs, design measurement plan for A/B Experiments, and deliver clear, actionable insights that influence product roadmaps and go-to-market decisions. You will operate as a trusted partner to Product, Design, Engineering, Strategy, and Data & Analytics stakeholders.

Job Responsibilities

  • Deep-Dive Analytics: Conduct rigorous deep-dive analyses of digital journeys, funnels, and feature performance to identify growth opportunities, quantify value (impact sizing), define success metrics, and prioritize analytics recommendations aligned to strategic goals i.e. CSAT, engagement, deepening, retention.
  • Experimentation & Measurement: Work on analytical plans that support A/B testing and experimentation; partner with cross-functional teams to define hypotheses, success criteria, guardrails, and post-test readouts that drive decisive action.
  • Data Storytelling & Executive Communication: Translate complex analyses into clear, compelling narratives and visualizations; communicate insights, trade-offs, and recommendations in a way that influences senior stakeholders and accelerates roadmap decisions.
  • Data Quality, Integrity & Instrumentation: Ensure data integrity and consistency across analytics platforms; partner with data engineering to improve event instrumentation, data collection, pipelines, documentation, and governance to enable scalable, trusted measurement.
  • Strategic Discovery Support: Partner with QUAD and product teams to lead discovery - formulate problem statements, size opportunities, define success metrics, and track outcomes.


Required Qualifications, Capabilities, and Skills

  • Bachelor’s degree required in data science, mathematics, statistics, econometrics, engineering, economics, or related quantitative fields with 3+ years of experience analyzing customer experiences and/or digital products/usage, with demonstrated ownership of end-to-end analytics deliverables (problem framing → analysis → recommendation → impact tracking).
  • Proven track record of problem-solving using data and building new analytics capabilities (metrics, dashboards, experimentation measurement, analytical frameworks).
  • Strong ability to translate quantitative outputs into actionable business insights and influence decisions through structured communication and data-driven storytelling.
  • Advanced proficiency in querying large-scale datasets using SQL and/or Python; ability to work effectively with big data platforms and partner with engineering teams.
  • Demonstrated expertise in digital analytics (journey/funnel analysis, segmentation, feature adoption, retention).
  • Excellent written, verbal, and presentation skills with experience communicating effectively with diverse stakeholders, including senior leaders.


Preferred Qualifications, Capabilities, and Skills

  • Hands-on experience with generative AI solutions, including large language models, retrieval-augmented generation, and agentic AI frameworks.
  • Experience working in Big Data environments (e.g., Snowflake, AWS) and collaborating with data engineering on scalable data products.
  • Familiarity with modern analytics platforms and instrumentation practices (event taxonomies, tracking plans, governance).
✕ position closed

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