Quantitative Software Engineer, Learning Engineering
Role details
Job location
Tech stack
Job description
deliver world-class AI/ML capabilities and integrate new and evolving technologies into our internal ecosystem, advancing our investment management business. You will take on the following responsibilities: Become an authority for the systems underpinning our research areas (ML, Finance, and/or quantitative algorithms) and help evolve these components Work closely with our research partners to conceptualize and iterate within new areas of research and development. Quantitative Engineers can have a diverse mandate including: Model development: prototyping, testing, and implementing models utilized across Two Sigma Quantitative systems: designing new architectures and/or developing systems that power research and trading activities at Two Sigma Quantitative tooling: developing and scaling the tools, frameworks, and libraries that are used by our teams to conduct research and build models - improving performance optimization and scalability of these capabilities You should possess the
Requirements
following qualifications: BS in Computer Science, Applied Mathematics, or related technical field Minimum 1 year of experience required; 3-10 years of experience preferred Professional experience building quantitative software across at least one of the following areas: quantitative finance, math/stats/numeric methods, and machine learning/deep learning Experience applying technologies and libraries such as NumPy, SciPy, or scikit-learn Experience with scientific computing and algorithm development Knowledge of scripting languages such as Python A background in building large-scale, real-time, and distributed applications is desired While we analyze the data-rich domain of finance, financial experience is not a requirement ", "salary_raw": "Row(double=None, string=None)"}