About the role
from listingTurn data into sales insights and intelligent workflows that help our Asset and Wealth Management teams make better decisions.
Join a high-growth Business Intelligence and Analytics team where your work directly shapes commercial strategy through data. You will turn complex datasets into clear insights, build scalable tools, and introduce automation that helps teams act faster. If you enjoy partnering with stakeholders, telling compelling stories with data, and delivering measurable outcomes, this role offers broad exposure and meaningful impact.
As a Quant Analytics Senior Associate – Business Intelligence at JPMorganChase within Asset and Wealth Management, you will support the Global Liquidity and North America Institutional Sales teams with performance insights and strategic recommendations. You will partner with sales leadership and cross-functional teams to define success metrics, improve decision-making, and deliver timely intelligence.
You will contribute to modern analytics capabilities, including automation and artificial intelligence (AI)-enabled workflows, while maintaining a strong focus on data quality, governance, and business outcomes.
Job responsibilities
Deliver actionable performance insights for the Global Liquidity and North America Institutional Sales teams to improve sales effectiveness
Build and maintain sales enablement tools that provide timely intelligence and clear recommendations
Develop and operationalize AI-enabled insights and workflow enhancements that improve decision-making speed and quality
Analyze large, complex datasets to identify trends, opportunities, and drivers of commercial outcomes
Prototype statistical or machine learning models to support strategic business objectives and measurement
Partner with technology teams to define data requirements and scale data models with appropriate lineage and governance
Present clear, compelling stories with data and translate findings into recommendations for senior stakeholders
Required qualifications, capabilities and skills
Three years of hands-on coding experience using Python, PySpark, and SQL
Experience delivering business intelligence or analytics solutions that drive measurable business outcomes
Working knowledge of AI concepts and practical applications in analytics, reporting, or sales enablement
Experience working in Agile delivery environments with cross-functional product teams
Proven experience designing, developing, and monitoring key performance indicators and performance measurement frameworks
Strong stakeholder management and communication skills across business and technology partners
Strong analytical and problem-solving skills, with the ability to work iteratively through evolving requirements and complex datasets
Preferred qualifications, capabilities and skills
Experience in asset management or financial services, including exposure to distribution or institutional sales organizations
Bachelor’s degree in business, analytics, data science, computer science, artificial intelligence, or a related discipline
Proficiency with Microsoft Excel and Microsoft PowerPoint for analysis and stakeholder-ready storytelling
Proficiency with Qlik Sense or Tableau for data visualization and self-service reporting