Compliance - Quant Analytics Senior Associate

JPMorgan Chase & Co.•Newark, DE

About The Position

As a Senior Associate in Strategic Data Analytics within the Compliance, Conduct and Operational Risk (CCOR) organization, you will help lead the design, development, and enhancement of scalable analytics, automation, and technology-enabled solutions that support data movement, inventory management, control monitoring, and operational decision-making across multiple compliance spaces. In this role, you will need to be a strategic, detail-oriented, and technically capable professional who can navigate complex and ambiguous problems, translate business needs into practical solutions, and collaborate effectively with cross-functional global teams. Additionally, you will be responsible for identifying and resolving inefficiencies and control gaps, defining data quality standards, and building automation and data-driven improvements. This role will require you to have the ability to take ownership of deliverables, make sound judgment-based decisions with minimal oversight, communicate clearly with stakeholders, and help deliver reliable solutions in an evolving environment. You will be part of an energetic team that values collaboration, ingenuity, continuous learning, and adaptability.

Requirements

Bachelor's degree in Computer Science, Data Analytics, Information Systems, Finance, Business, or a related field.
5+ years of experience in data analysis, process improvement, compliance, operations, technology, or a related discipline.
Ability to independently identify, decompose, and solve complex technical and business problems.
Foundational proficiency in least one programming language such as SQL, Python, Java, or JavaScript.
Experience implementing data quality frameworks, validation controls, and governance processes to ensure accuracy and auditability of analytical outputs.
Strong collaboration and interpersonal skills with a track record of working effectively across distributed teams, functions, and seniority levels.
Experience with logical and physical data modeling, schema design, and data architecture principles in enterprise environments.
Hands-on experience with Databricks, Apache Spark, or similar distributed data processing frameworks for building and maintaining production data pipelines.
Self-motivated, independent, and action-oriented with the ability to influence across the firm.
Ability to work independently and as part of a team while demonstrating adaptability in a dynamic environment with changing priorities, tools, and business needs.
Proficient in other MS Office applications (Outlook/Word/PowerPoint).

Nice To Haves

Strong proficiency in SQL and Python; experience with Databricks, Snowflake or other big-data query tools
Experience in developing, maintaining, and optimizing Tableau/ThoughtSpot dashboards and reports for business users
Strong written and oral communication skills; ability to communicate effectively with all levels of management and partners from a variety of business functions
Demonstrated proficiency in Microsoft Excel, including advanced functions and data analysis capabilities.

Responsibilities

Lead the identification, decomposition, and resolution of complex, ambiguous problems across workflows, driving root-cause analysis and designing scalable solutions.
Proactively research and learn new emerging technologies, methodologies, and business processes to inform innovation strategy and continuously improve team capabilities.
Define and enforce data quality standards, validation controls, and audit frameworks to ensure that alerts, dashboards, and AI-driven outputs are trusted, accurate, and compliant.
Develop automation solutions using Python, Java, or JavaScript to streamline investigation workflows, data pipelines, and operational processes.
Adapt to evolving priorities and requirements while taking ownership of deliverables and project outcomes, and fostering a culture of accountability, transparency, and continuous improvement.
Design and build scalable data pipelines and ETL processes using Databricks and Spark to support analytics, operational reporting, control monitoring, and reoccurring workflows.
Communicate complex technical concepts, project statuses, business needs, and strategic recommendations clearly to senior leadership, business stakeholders, and cross-functional partners.