State Street

State Street

Lead Quantitative Software Engineer / Front-Office Quant Developer, VP

Boston, Massachusetts, USA · Vp

Sponsorship not specifiedDetected 15 days ago
PythonJavaC++GitSQLCI/CDLinuxPandasNumPyJiraValuation

About the role

  • The role requires experience in working with diverse technologies such as C++, Java, Python as well a wide range of financial products.
  • Financial Products: Interest Rate Swaps (IRS), Basis Swaps, Swaptions, Exotic Options, Forward Rate Agreements (FRAs), and Inflation-linked products.
  • Quantitative Concepts: Stochastic Calculus, Monte Carlo Simulations, Finite Difference Methods, Yield Curve Bootstrapping, Libor Market Model (LMM), and Hull-White model calibration.

Responsibilities

  • Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability.

Skills

  • Python, time series databases such as kdb+/q, SQL, Linux, Boost, QuantLib, Nvidia CUDA and / or OpenCL
  • Linux environment, kdb+/q time-series database, distributed grid computing, Git, Jira, CI/CD pipelines.
  • Education & Certifications
  • Master of Science in Financial Engineering (MSFE)
  • Bachelor of Science in Computer Science & Mathematics
  • Infrastructure & Tools: Linux environment, kdb+/q time-series database, distributed grid computing, Git, Jira, CI/CD pipelines.

Compensation

  • Employees are eligible to participate in State Street's comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disab

Benefits

  • State Street's comprehensive benefits program, which includes:

Visa & Work Authorization

  • gin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military a
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This listing is sourced directly from State Street's careers page and normalized into a canonical job model.