About

We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance.

Cubist’s data services group is looking for Data Operations Analyst to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.

This exceptional individual will join a global team of Data Operations Analysts who play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments.

Responsibilities

• Level 1 support for thousands of mission critical data pipelines.
• Day-to-day operations including data validation, data entry tasks, data cleaning, security audits and reporting.
• Incident management including user communication and reporting for management.
• Developing tools, documentation, and processes to assist with daily operations and support.
• Support for complex permission and entitlements operations across many different systems.

Requirements

• Bachelor’s degree with a concentration in Computer Science or related discipline.
• 3+ years of experience working in a client facing support or operations role.
• Experience working in Windows and Linux environments both on-prem and in AWS.
• Experience with SQL Server and Python.
• Financial industry experience preferred but not required.
• Attention to detail and a love of process.
• Strong organization, communication, and interpersonal skills.
• Commitment to the highest ethical standards.

The annual base salary range for this role is $100,000-$150,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.