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Minimum Requirements: Bachelor’s degree or the equivalent in Computer Science, Applied Mathematics, Computational Finance and Risk Management, or related field plus 1 year of experience in finance, operational risk management, software engineering or related experience. Must have experience with developing, maintaining & troubleshooting codebases, including code review & implementing test cases for code validation. Must have experience with programming in Python, including numerical & data analysis libraries (Pandas, Numpy) for quantitative analysis. Must have experience with querying, manipulating & managing data using database tools, including processing & profiling large datasets from multiple sources, data cleaning, quality checking & validation. Must have experience with applying statistical analysis methods including regression, correlation & other quantitative methods for evaluating strategy behavior & operational risks. Must have experience with operating in Linux environments, including basic commands for file operations, process management, text search & data processing. Must have experience with designing & building automated tools, alerts & analytical reporting for data-driven decision-making. Must have experience with monitoring operational processes & system outputs, identifying & escalating anomalies or issues. Must have experience with preparing technical documentation, research reports & analytical findings & collaborating with cross-functional teams including investment, engineering & operations stakeholders. Must have experience with conducting root-cause investigations of operational issues. Must pass company’s required skills assessment. Employer will accept any amount of experience with the required skills.
Rate of pay: The base pay for this role will be between $150,000 and $200,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
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