Join a Payments Data and Analytics team that builds data products used to improve how clients run and grow their businesses. You will work on high-impact analytics and generative AI solutions across large, complex payment data sets. You will collaborate with product, engineering, and business partners to deliver insights and decision tools. This role offers opportunities to use modern data platforms and develop client-facing solutions at scale.
As a Data Scientist Associate in Payments Data and Analytics, you execute analytics initiatives that improve payment performance and enable product innovation. You translate business goals into data requirements, models, and measurable deliverables. You develop analyses, data products, and generative AI solutions that produce actionable insights for stakeholders and clients. You partner with cross-functional teams to productionize resilient analytics and AI applications. You contribute to continuous improvement through strong documentation, testing, and change-control practices.
Job responsibilities
- Define analytic projects by translating business objectives into clear problem statements, success metrics, and delivery plans.
- Develop analyses and deliverables that align to agreed requirements, timelines, and stakeholder expectations.
- Build datasets, queries, and reusable tables to enable scalable analytics and reporting.
- Create visualizations and decision-support tools that communicate insights to technical and non-technical audiences.
- Recommend actionable performance improvements to clients based on payment and transaction behavior patterns.
- Productionize interactive analytics and AI applications with a focus on resiliency, usability, and supportability.
- Identify opportunities to enhance existing analytics products and propose improvements grounded in data.
- Partner with data owners and platform teams to evolve data models for future analytics and product capabilities.
- Collaborate with unit leaders, end users, and development teams to confirm business value and prioritize work.
- Apply quality assurance, change-control, and testing practices for updates to code, models, and data products.
- Support users by addressing questions, incorporating feedback, and improving documentation and training materials.
Required qualifications, capabilities, and skills
- Bachelor’s or master’s degree in engineering, computer science, statistics, mathematics, or a related quantitative field.
- 2 years of experience delivering analytics in a big data environment in a self-directed role.
- Experience using SQL (Snowflake) and Python to build analyses and data products.
- Experience applying generative AI tools or techniques to analytics, automation, or decision-support use cases.
- Understanding of algorithms, data structures, and software engineering fundamentals.
- Demonstrated ability to define key performance indicators (KPIs) and performance metrics from data.
- Experience sourcing, assessing, and shaping data for analysis, including improving data structures and query performance.
- Ability to document analytics requirements, assumptions, and deliverables in partnership with stakeholders.
- Strong communication skills with the ability to present insights clearly to varied audiences.
- Strong problem-solving skills with the ability to translate strategy into measurable deliverables.
Preferred qualifications, capabilities, and skills
- Experience in payments, merchant services, or adjacent transaction-driven industries.
- Experience building and evaluating generative AI solutions (for example, prompt design, retrieval-augmented generation patterns, or model evaluation).
- Experience deploying analytics or AI applications into production with monitoring and support practices.
- Experience building data visualizations and dashboards for business users.
- Experience partnering with product and engineering teams to deliver analytics capabilities on shared platforms.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Bachelor's or master's degree in engineering, computer science, statistics, mathematics, or a related quantitative field.
- Two years of experience delivering analytics in a big data environment in a self-directed role.
- Experience using SQL and Snowflake to build analyses and data products.
- Experience using Python to build analyses and data products.
- Experience applying generative AI tools or techniques to analytics, automation, or decision-support use cases.
- Understanding of algorithms, data structures, and software engineering fundamentals.
- Ability to define KPIs and performance metrics from data.
- Experience sourcing, assessing, and shaping data for analysis, including improving data structures and query performance.
- Ability to document analytics requirements, assumptions, and deliverables with stakeholders.
- Strong communication skills for presenting insights to varied audiences.
- Strong problem-solving skills and ability to translate strategy into measurable deliverables.
- Experience in payments, merchant services, or adjacent transaction-driven industries.
- Experience building and evaluating generative AI solutions, including prompt design, retrieval-augmented generation, or model evaluation.
- Experience deploying analytics or AI applications into production with monitoring and support practices.
- Experience building data visualizations and dashboards for business users.
- Experience partnering with product and engineering teams to deliver analytics capabilities on shared platforms.
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
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Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
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Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
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