Duties: Conduct non-routine analyses, including data gathering from large and complex data sets and employ advanced statistical methods to improve the quality of Two Sigma’s products. Build automated data pipelines to ensure the seamless flow of data across multiple, disparate production environments. Develop, run, and maintain operational metrics and initiative tracking that link the impact of technology efforts to business outcomes. Work alongside leaders across Product Management, Engineering, Finance and Corporate functions to help drive high decision quality across an aligned cross-functional strategy. Work cross-functionally with Engineering, Product Management and Business colleagues to identify opportunities for improvements across Two Sigma’s engineering organization and products. Drive Engineering Leadership monthly reporting cadence covering technology capabilities and financials - by being the subject matter expert on the underlying data, metrics and visualizations in the reporting framework. Product Manage the reporting portal for engineering and engineering finance, design the UX/UI, and create all necessary pipelines to automate disparate data sources. Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) and convey findings at multiple levels including executive leadership, managers, and peers through visual displays of quantitative information.

Minimum education and experience required: Master’s degree or equivalent in Computer Science, Computer Engineering, Management Information Systems, or related field plus 3 years of experience in data analysis, or related experience; OR Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Management Information Systems, or related field plus 5 years of experience in data analysis, or related experience.

Skills required: Must have experience with Data Analysis, including analyzing large data sets, identifying trends, anomalies and drawing conclusions from the data as well as using statistical techniques such as regression analysis, time-series analysis, and hypothesis testing to make better business decisions. Must have experience with Database Management (including database management systems like postgres, Oracle, Big Query) and with Database Design. Must have experience with SQL, including writing complex queries, as well as fetching, manipulating and analyzing large data sets. Must have experience with Data Visualization (including UI/UX experience for SaaS retail products) using data visualization tools (such as Tableau, Power BI, and Excel) as well as creating charts, graphs, and dashboards that are visually appealing and easy to understand. Must have experience with Data Modeling, including designing and developing reliable data pipelines to produce datasets that can be used for further analysis. Must have experience with Programming, including scripting languages (such as Python or R) to clean, transform, and manipulate large datasets as well as tools (like Jupyter Notebooks) for rapid data analysis. Must have experience with Data Quality Control, including designing and implementing measures to ensure the accuracy of data and reports. Must have experience holding business functions, including finance experience or have held P&L responsibility, as well as experience translating business needs and implementing engineering solutions. Must have experience with Project Management, including managing multiple projects simultaneously, prioritizing tasks, communicating status, and meeting deadlines. Must have experience with presenting at executive management levels, partnering cross functionally. Must have experience with structuring work and defining priorities in rapidly changing and fast paced environments. Employer will accept any amount of experience with the required skills.

The base pay for this role will be between $165,000 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.