The majority of their systems operate on Linux, with Python being the predominant language utilized, incorporating the full scientific stack including NumPy, SciPy, Pandas, statsmodels, and scikit-learn among others. For high data throughput systems, we employ Java. MongoDB and MS SQL serve as our primary storage solutions.
Qualifications:
- 5-7 years of professional experience in software engineering, with a preference for expertise in quantitative applications
- Advanced proficiency in Python and Pandas, coupled with competence in related scientific libraries like NumPy, SciPy, statsmodels, and scikit-learn
- Demonstrated track record in developing mission-critical production systems, with expertise in best practices for testing, monitoring, and deployment
- Strong familiarity with Linux platforms and a solid grasp of Git
- Working understanding of one or more pertinent database technologies, such as MS SQL, Postgres, or MongoDB
