Data Scientist, Senior Associate

JPMorgan Chase & Co.; Kentucky; On-site; USD 90,000 - 130,000; Full time

Job summary

JPMorgan Chase & Co. in the United States is seeking a Data Science Senior Associate to design and operate resilient data products and pipelines that support hypothesis-driven analyses across the product development lifecycle.

You will build scalable batch and streaming pipelines, implement data quality controls, and work with Airflow, Databricks, and dbt to deliver trusted metrics for cross-functional partners in product, engineering, and analytics.

Qualifications

• Bachelor’s degree in CS/Engineering or equivalent practical experience.
• 3+ years building production data solutions with ownership and delivery.
• Strong engineering fundamentals and development lifecycle.
• Strong data modeling (dimensional, normalized, event-based).
• Experience with Databricks and Spark/PySpark.
• Strong SQL; dbt experience and testable data codebases.
• Experience operating orchestration pipelines (Airflow).

Responsibilities

• Build and operate scalable batch/streaming pipelines with SLAs and incident response.
• Create and maintain trusted data products with clear ownership and docs.
• Deliver metrics and datasets for AI adoption and measurement.
• Implement data quality and governance controls (validation, lineage, retention).
• Orchestrate workflows in Airflow with backfills and retries.
• Model/transform data using SQL and dbt for trusted reporting.
• Write production-grade Python/PySpark with tests and performance tuning.
• Collaborate with stakeholders to define requirements and success criteria.
• Contribute to engineering best practices and observability.
• Mentor peers through reviews, docs, and knowledge sharing.

Skills

Data pipelines

Data modeling

SQL

dbt

Airflow

Databricks

Spark/PySpark

Education

Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Tools

Databricks

Job description

Job Description

We are seeking a Data Science Senior Associate focused on building and operating resilient datasets, pipelines, and reusable metrics that support hypothesis-driven analyses and experiments across the product development lifecycle (PDLC)

In this role, you will be hands-on in designing, developing, and maintaining data products that are reliable, observable, and well-documented—enabling partners across product, engineering, and analytics to measure what’s driving value, where friction exists, and how operating-model changes impact outcomes as teams adopt more agentic ways of working. You’ll contribute to engineering standards and help raise the quality bar through strong delivery and collaboration.

Job Responsibilities

• Build and operate scalable batch/streaming pipelines with SLAs, monitoring, and incident response participation (as needed).
• Create and maintain trusted data products (dimensions, event models, marts) with clear ownership and documentation.
• Deliver metrics and feature-ready datasets for AI adoption/productivity measurement; manage definition changes over time.
• Implement data quality and governance controls (validation, reconciliation, lineage, access, retention, auditability).
• Orchestrate workflows in Airflow (or equivalent), including backfills and retries.
• Model/transform data using SQL and dbt (or equivalent) for trusted reporting and repeatable measurement.
• Write production-grade Python/PySpark with testing, performance tuning, and maintainable design.
• Partner with cross-functional stakeholders to define requirements, success criteria, and metric interpretation across finance, PDLC/SDLC, and AI tool logs.
• Contribute to engineering best practices (version control, code review, CI/CD, runbooks) and improve observability and cost/performance.
• Mentor peers through reviews, documentation, and knowledge sharing (no formal people management).

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years building production data solutions; strong ownership and delivery.
• Strong engineering fundamentals (OOP, testing, development lifecycle).
• Strong data modeling skills (dimensional, normalized, event-based).
• Experience with Databricks and/or Spark/PySpark.
• Strong SQL; experience with dbt (or equivalent) and building testable data codebases.
• Experience operating orchestration pipelines (Airflow or equivalent).
• Proven ability to build and maintain reliable metrics as sources/definitions evolve.
• Effective delivery in ambiguous, multi-stakeholder environments.

Preferred Qualifications

• Experience with modern lakehouse/warehouse patterns and broader cloud data platforms (e.g., Databricks, Snowflake).
• Experience with BI/semantic layers and metrics management practices.
• Exposure to experimentation or hypothesis-driven analytics approaches (e.g., measurement design to support tests, rollouts, and pre/post evaluation); deep causal specialization not required.
• Experience improving observability (data freshness/SLA monitoring, lineage, alerting) and contributing to operational maturity (runbooks, incident follow-ups).

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

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.

Equal Opportunity Employer/Disability/Veterans