Data Products – Vice President, APAC Chief Data & Analytics Office at JPMC Candidate Experience page

Singapore, Singapore, Singapore -

Full Time

Start Date

Immediate

Expiry Date

07 May, 26

Salary

0.0

Posted On

06 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Product Development, Analytics, Product Management, Collaboration, Data Governance, APIs, Cloud-Native Frameworks, Data Strategy, Problem Solving, Technical Design Principles, Stakeholder Management, Data Ingestion, Data Transformation, Compliance, Mentoring, Performance Monitoring

Industry

Financial Services

Description

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is pivotal in advancing the firm's data and analytics capabilities, ensuring strong adherence to data & AI risk & control while enabling the data & analytics strategy for superior decision-making and business outcomes to serve our clients and markets. By leveraging data & AI/ML, the CDAO develops innovative solutions to support commercial goals, enhance productivity, and manage risks. The Asia Pacific Chief Data & Analytics Office (CDAO) advances the firm’s data and analytics strategy, platforms, solutions, capabilities, and governance to deliver trustworthy, responsible, innovative, and commercially value outcomes across the APAC markets and businesses. As Data Products, Vice President, the role is expected to play a key role in the design, development, and delivery of innovative data products that support the firm’s data and analytics strategy. This will involve executing product roadmaps, collaborating with cross-functional teams, and ensuring high-quality, scalable solutions that meet business needs. There will be a focus on driving operational excellence, supporting product adoption, and contributing to a culture of continuous improvement within the data product team. Key Responsibilities Support the execution of the data product strategy by translating business requirements into actionable product features and enhancements, ensuring alignment with overall data and analytics objectives. Collaborate with internal stakeholders to gather requirements, prioritize product features, and ensure successful integration of internal and external data sources. Contribute to the development and enablement of APIs and self-service data access capabilities, empowering users to leverage platform features efficiently. Manage data product delivery workflows, ensuring products are validated, documented, and published according to established standards and timelines. Support the implementation and optimization of enterprise data platforms (e.g., Databricks, Snowflake), focusing on scalable data storage, processing, and analytics. Assist in architecting solutions for data ingestion, transformation, and analytics, leveraging distributed computing and cloud-native frameworks under the guidance of senior leadership. Champion data governance best practices, including metadata management, data cataloging, and compliance with regulatory requirements. Work with compliance and risk teams to ensure data products and platforms adhere to privacy, protection, and auditability standards. Mentor junior team members on product development best practices, fostering skill development and knowledge sharing. Monitor product performance and user adoption, providing insights and recommendations for enhancements to drive business value. Track and report on key performance indicators for data products, supporting continuous improvement and growth. Promote a culture of technical excellence and innovation within the data product team Required Qualifications, Capabilities, and Skills Bachelor’s degree in Computer Science, Data Science, Mathematics, or related field. At least 8 years of experience in data product development, analytics, or technology delivery. Solid understanding of the product development life cycle and technical design principles. Experience collaborating with cross-functional teams and managing stakeholder requirements. Strong problem-solving skills, with experience in data strategy, product management, or analytics within financial services or a related industry. Working knowledge of data, AI, and emerging technologies. Strong analytical skills and attention to detail. Excellent verbal and written communication skills; able to communicate effectively with technical and non-technical stakeholders. 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. Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Responsibilities

The role involves executing product roadmaps and collaborating with cross-functional teams to deliver innovative data products that align with the firm's data and analytics strategy. It also includes managing workflows for product delivery and championing data governance best practices.