Client Analytics - BI Developer
crypto:analyticsengineeringIC4Engineering
Compensation
Not disclosed
About AQR Capital Management
AQR is a global investment firm built at the intersection of financial theory and practical application. We strive to deliver concrete, long-term results by looking past market noise to identify and isolate the factors that matter most, and by developing ideas that stand up to rigorous testing. By putting theory into practice, we have become a leader in alternative strategies and an innovator in traditional portfolio management since 1998.
At AQR, our employees share a common spirit of academic excellence, intellectual honesty, and an unwavering commitment to seeking the truth. We’re determined to know what makes financial markets tick – and we’ll ask every question and challenge every assumption. We recognize and respect the power of collaboration and believe transparency and openness to new ideas lead to innovation.
The Team
The Client Analytics Team is responsible for the design, development, enhancement, and maintenance of client data analytics platform that delivers critical data to Finance, Business Development, and Operations teams.
We are a small, highly motivated, and productive group. We work closely with business stakeholders, and our solutions are highly visible across the firm—demanding a strong focus on precision and reliability.
Your role
AQR is seeking an Analytics & Data Visualization Associate to join our Client Analytics Engineering team. This role focuses on building and maintaining Tableau dashboards, developing Python-based data pipelines, and ensuring the quality and reliability of data used in analytics and reporting. The position involves close collaboration with business and engineering teams.
Design, develop, and maintain dashboards using Tableau.
Partner with stakeholders to gather requirements and translate them into clear, actionable visualizations.
Develop and maintain Python-based scalable data pipelines.
Ensure quality, reliability, and efficient processing of datasets.
Investigate and r