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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist, Senior Associate - **Company:** JPMorgan Chase & Co. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Code Review, Continuous Integration, Python (Programming Language), Object-Oriented Software Development, Operational Databases, Performance Tuning, Systems Development Life Cycle, Cloud Services, Standard Sql, Runbook, SQL Databases, Snowflake, Apache Spark, Data Layers, Pyspark, Information Technology, Software Version Control, Databricks - **Published:** September 19, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28032767/Data-Scientist-Senior-Associate-Ohio-All-Cities-7463 ## About the Role * 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). ## 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., * 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). ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Technical Documentation - How Can I Write Them Better and Why Should I Care?](https://www.wearedevelopers.com/videos/681-technical-documentation-how-can-i-write-them-better-and-why-should-i-care) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)