Product Manager, ED - Client Engagement

JPMorgan Chase & Co.
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - AI, ML & Data Science

Data Science Manager

Technology Project Manager

Machine Learning Manager, Munich

Senior Technical Product Development Engineer

Product Director - Digital Health

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

Job Description

The Client Engagement Lead for the Chief Data & Analytics Office (CDAO) Platform will play a pivotal role in supporting the data, AI, and analytical needs of one of the largest financial institutions. This role is part of the Chief Data & Analytics Office (CDAO) at JPMorgan Chase, which is responsible for accelerating the firm's data and analytics journey. The Client Engagement lead is responsible for relationship management, solution design and implementation of integrated plans between a JPM LOB or Corporate Function and the CDAO Platform. The position requires a strategic thinker with exceptional influencing and communication skills, to drive adoption of firmwide solutions for data, governance and AI.

Job Responsibilities

  1. Create awareness through clear and concise messaging about the platform's capabilities and benefits.
  2. Drive adoption of platform capabilities to maximize value for clients.
  3. Contribute to the overall success of the CDAO Platform by aligning client strategies with business objectives.
  4. Develop and maintain strong relationships with clients, acting as a trusted advisor.
  5. Develop trust and rapport with stakeholders to ensure client satisfaction and success.
  6. Convey complex information clearly through excellent verbal and written communication skills.
  7. Present ideas and solutions effectively to diverse audiences.
  8. Be well-versed in platform architecture, solution engineering, and cloud services/capabilities.
  9. Provide technical guidance and support to clients, ensuring solutions are effectively implemented.
  10. Track and report on key performance indicators (KPIs) related to platform integration and customer satisfaction.
  11. Clearly articulate product capabilities that most effectively meet customer needs.

Required Qualifications, Capabilities, and Skills

  1. Proven experience in account management or a similar role within an enterprise financial or technology company.
  2. Expertise and experience in at least two of the following: data governance, data management, machine learning, GenAI, cloud platforms, or analytics.
  3. Excellent communication, relationship-building, and leadership skills.
  4. Technical proficiency in cloud services, platform architecture, and solution engineering.
  5. Strong project/program management skills and a strategic and commercial mindset.

About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals, and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

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.

About the Team

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.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.