Backend developer for a team working on development of a quantitative engine for analyzing financial data. In particular, the engine includes valuation of many asset classes and derivatives types, portfolio level value distribution and statistics, backtesting, and more.
The jobs will include processing of financial data, expansion of current engine capabilities (e.g. adding support for additional asset classes or derivative types), and implementation of new algorithms related to performance and risk measurement and analysis.
At least 5 years experience as a developer.
At least 3 years experience with scientific/data related development.
At least 1 year experience with python’s scientific stack, e.g. NumPy, Pandas, etc.
Undergraduate level knowledge of linear algebra, probability, and statistics. I.e. comfortable working with matrices, knowledge of common probability distributions, and understanding of statistical estimation.
Familiarity with quantitative finance modeling, e.g. Black-Scholes.
Experience with AWS.
Experience with distributed computing/big data (Dask, Spark, etc.).
Familiarity with AI/ML related modeling and tooling (PyTorch, TensorFlow, etc.).
Experience working in agile environments.
Experience with TDD.
Open-source contributions – strong bonus.