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Quantitative Developer - 2452889

Quantitative Developer - 2452889

2Bridge PartnersStamford, CT, US
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Job Description

Job Description

2Bridge has been engaged in the search for a direct-hire Quant Developer for an innovative FinTech company. The company has secured a significant Series A funding round and is expanding its team. It is looking for a Senior Quant Developer to enhance its technological capabilities as it scales.

Role Summary :

You'll play a crucial role in developing quantitative models and algorithms vital for the company’s financial products and services.

Compensation and Benefits : Our client offers Total Compensation between 250,000 and 350,000, split between a base and performance-based bonus. For the right person, there is potential for equity. They also offer a comprehensive benefits package including Medical, Dental, Vision, 401k, 24 days PTO, and all NYSE Holidays, Etc. This is as hybrid role, onsite, one day a week, in one of their offices in either NYC or Stamford.

Responsibilities :

  • Develop and enhance quantitative models and algorithms for performance and scalability.
  • Collaborate with teams to integrate quantitative solutions into broader system architectures.
  • Validate models for correctness and edge-cases.
  • Maintain market data handlers, data models, and valuation cache.
  • Stay updated with industry trends and incorporate advanced quantitative techniques as applicable.

Qualifications :

  • Bachelor’s or preferably an MS in Quantitative Finance, Computer Science, Mathematics, or a related field.
  • 3-5 years experience in Quantitative Development within financial services, specifically with Trade Cost Analysis in Fixed Income, Corporate Bonds, non-vanilla swaps, and other OTC Derivatives.
  • 5 years experience in Java or C#, .Net, Bonus points for expertise in Python.
  • Extensive experience with Analytics Libraries such as QuantLib, FinCad, Numerix, etc.
  • Experience with time series databases like OneTick, KDB, InfluxDB.
  • Experience with machine learning algorithms and their applications in financial modeling.
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