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Lead Quantitative Software Engineer
2 months ago
Overview: Selby Jennings is collaborating with a well-established Private Asset Manager seeking to recruit a Quantitative Software Developer. This role involves partnering with various systematic investment teams during a significant migration project. Following this transition, you will contribute to the development of innovative data processing and quantitative tools utilizing Python within a modern, scalable cloud computing environment. Furthermore, you will engage closely with Researchers and Portfolio Managers, addressing all facets of research and production code that underpin the investment strategies, from model development to portfolio optimization.
Required Qualifications:
- Bachelor's degree or equivalent required (Advanced degrees in computer science, data science, engineering, mathematics, or related fields are preferred)
- Minimum of 5 years of experience in Python, including package development, with at least 7 years of overall software development experience
- Proficiency in SQL and database development, preferably with relational databases
- Strong familiarity with version control systems, particularly git
- Knowledge of statistical methods and experience with optimization libraries (including open-source libraries like cvxpy and commercial solvers such as Gurobi)
Preferred Skills:
- Experience with MATLAB
- Understanding of contemporary CI/CD DevOps practices and orchestration tools like Azure DevOps, Airflow, Kubernetes, and Docker
- Experience with cloud-based large data platforms, including Databricks, Synapse, and Data Lakehouse
Key Responsibilities:
- Enhance and maintain the existing research platform and strategy/portfolio applications by developing, testing, and deploying production model code.
- Collaborate with researchers and investment professionals to provide operational support for quantitative models.
- Assist in transitioning code to a new Python-based quantitative research platform, recommending modern architectures in partnership with other Technology Team members to determine optimal end-to-end solutions.
- Adhere to industry-standard best practices for software design and implementation, lead internal code review sessions, conduct code analysis, and proactively identify software risks.
- Design and implement efficient end-to-end data and analytical solutions that meet internal business needs, utilizing a Python stack.
- Actively engage in Python/new platform working groups and participate in agile/scrum activities.