Quantitative Equity Analyst Reliability Engineering

• Design, implement and test production processes to run the alpha and risk, portfolio optimization and market implementation processes.
• Design robust, high performance and effective process orchestration.
• Monitor production health and respond to critical issues in a timely manner.
• Effectively communicate real-time production issues to portfolio managers, traders and researchers.
• Identify computational bottle necks and improve run speeds in production systems.
• Collaborate with investment teams to ensure their process needs are being met.
• Find and evaluate areas for process improvements.
• Assess and evaluate data quality of production processes.
• Maintain process repos, clean code and tools within production processes.

• Construct and run algorithms to explore and assess data effectively.
• Validate structured and unstructured data sets for data quality.
• Design and test data loaders and security matching processes and specifications.
• Perform data analysis and provide data expertise to support researcher’s projects.
• Facilitate production machine learning operational pipelines with effective and timely auditing and analysis.
• Enable accessibility and clarity within our data assets through robust documentation and data scrubbing.
• Develop robust methodologies for assessing and analyzing data in time critical production environments.
• Respond to and mitigate vendor data issues effectively in a production setting.
• Collaborate with cross-functional teams to integrate traditional and alternative data into existing analytical frameworks and decision-making processes.
• Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner.

• Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation.
• Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements.
• Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work.
• Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts.
• Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities.
• Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset.
• Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields.

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