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Data and Analytics - Quant Analytics Senior Associate
JPMorgan Chase · Columbus, OH, United States
About The Role
Join a team that seeks for talented and highly motivated individual with exceptional data analysis skills.
As a Quant Analytics Senior Associate, within the Data and Analytics team, you will lead the analytics book of work and collaborate with a cross-functional team to support the Product and work closely with partners across Finance, Customer Experience, Design, Software Engineering, and Product Ownership.
Job Responsibilities
- Build holistic insights by integrating customer, account, digital, financial, and operational data sets to inform strategic decision-making.
- Import, clean, transform, and validate data from multiple sources to prepare for advanced analytics and modeling.
- Scope, implement, and track new features and enhancements within the collections journey to optimize customer experience and operational efficiency.
- Identify customer interactions and events across various channels to gain a deeper understanding of customer journeys and pinpoint friction points.
- Utilize a range of analytical and statistical tools—including Alteryx, Excel, SQL, Python, and Tableau—to analyze and interpret trends and patterns in complex data sets.
- Support the creation and delivery of presentations that summarize key insights and actionable conclusions, often tailored for executive audiences.
- Collaborate with business stakeholders to translate strategic objectives into actionable analytics initiatives and measurement frameworks and lead cross-functional projects, coordinating with product, technology, and business teams to deliver impactful analytics solutions.
Required Qualifications, Capabilities, and Skills
- Bachelor’s degree required, with a strong academic background and at least 4 years of experience building analytical solutions that integrate multiple data inputs from diverse sources, particularly in Marketing, Customer Journey, Operations, or Finance; Minimum of 2 years of hands-on experience in data analysis.
- Demonstrated technical expertise in data modeling, data analysis, and segmentation techniques.
- Proficient in Business Intelligence and analytical tools such as Alteryx and Tableau.
- Self-sufficient in querying and extracting data from enterprise databases and data lakes, including platforms such as Snowflake, GOS, and AWS Athena.
- Analytical rigor, with the ability to synthesize information across multiple platforms, systems, and organizations, and deliver superior data analysis.
- Champion the use of advanced analytics techniques, such as machine learning and predictive modeling, to uncover deeper insights and drive innovation.
- Establish and monitor key performance indicators (KPIs) to measure the effectiveness of analytics initiatives and inform ongoing strategy.
Preferred Qualifications, Capabilities, and Skills
- Experience developing financial business cases is highly desirable.
- Operational knowledge of Document Services Operations is a strong advantage.
- Background in analytics or experience within consumer or retail banking is preferred.
- Familiarity with AWS technologies is a plus.
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