As an Applied AI/ML Analyst within our dynamic team of innovators and technologists, you will revolutionize how the Bank services and advises clients, deepen client engagements, and promote process transformation. You will analyze existing processes and vast amounts of data to design autonomous AI agents. We seek individuals passionate about leveraging advanced data analysis, statistical modeling, and AI/ML techniques to solve complex business challenges through high-quality, cloud-centric software delivery. Our culture thrives on experimentation, continuous improvement, and learning. You will work in a collaborative, trusting, and intellectually stimulating environment—one that values diversity of thought and fosters creative solutions that serve the best interests of our global clientele.
Job Responsibilities
- Build and maintain end-to-end batch and streaming data pipelines (ingestion → transformation → curation → serving) on AWS.
- Develop scalable transformations using Spark (PySpark/Scala) and SQL, optimizing for performance, reliability, and cost. Implement and optimize Snowflake solutions (schemas, tables, views, micro-partitioning/clustering considerations, warehouse sizing, query tuning, data sharing patterns where applicable).
- Understanding of data models for enterprise analytics (dimensional/star schemas, normalized models; applying standard banking data concepts where relevant). Create robust orchestration and scheduling (e.g., Airflow/MWAA, AWS Step Functions, etc.) with monitoring, alerting, retries, and operational runbooks.
- Ensure data quality through validation checks, reconciliation, and controls (e.g., completeness, timeliness, accuracy, deduplication). Implement security and governance controls suitable for banking: encryption, least-privilege access, auditability, data retention, and lineage/documentation.
- Collaborate with stakeholders across technology, risk, compliance, analytics, and product to translate requirements into reusable, well-defined datasets and support production operations: incident triage, root-cause analysis, performance tuning, and continuous improvement of pipeline stability.
- Collaborate with data science and ML teams to design, build, and maintain scalable data infrastructure that supports the training, deployment, and monitoring of AI/ML models. Continuously evaluate and adopt emerging AI technologies to optimize ETL workflows, reduce manual effort, and enhance overall engineering productivity.
Required qualifications, capabilities, and skills
- Bachelors degree in a quantitative or technical discipline or significant practical experience in industry.
- Strong SQL skills (complex joins, window functions, query optimization, performance troubleshooting) and experience with AWS data services and cloud-native patterns (e.g., S3, IAM, KMS, Glue, Lambda, EMR, Step Functions, Kinesis/MSK—relevant mix).
- Solid understanding of data modeling and how model choices impact performance, usability, and governance.
- Practical experience with Snowflake (data loading, transformations, optimization, access controls). Proficiency in Python (or equivalent) for pipeline development, automation, and testing.
- Experience with Git and CI/CD practices; familiarity with engineering standards for code reviews and automated testing.
Preferred qualifications, capabilities, and skills
- Prior experience of developing solutions for Financial domain
- Exposure to distributed model training, and deployment
- Familiarity with techniques for model explainability and self-validation
- Hands-on development experience with Spark (PySpark preferred) for large-scale processing.
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 degree in a quantitative or technical discipline or significant practical industry experience
- Strong SQL skills (complex joins, window functions, query optimization, performance troubleshooting)
- Experience with AWS data services and cloud-native patterns (S3, IAM, KMS, Glue, Lambda, EMR, Step Functions, Kinesis/MSK)
- Practical experience with Snowflake (data loading, transformations, optimization, access controls)
- Proficiency in Python (or equivalent) for pipeline development, automation, and testing
- Experience building and maintaining end-to-end batch and streaming data pipelines (ingestion -> transformation -> curation -> serving)
- Solid understanding of data modeling for enterprise analytics (dimensional/star schemas, normalized models)
- Experience with orchestration and scheduling tools (Airflow/MWAA, AWS Step Functions) and operational runbooks
- Experience with Git and CI/CD practices, code reviews, and automated testing
- Prior experience developing solutions for the financial domain
- Exposure to distributed model training and deployment
- Familiarity with model explainability and self-validation techniques
- Hands-on development experience with Spark (PySpark preferred) for large-scale processing
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 — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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