Quant Developer/ Analyst

  • Jersey City, NJ
  • Posted 2 days ago | Updated 2 days ago

Overview

Hybrid
$70 - $80
Contract - Independent
Contract - 6 Month(s)
No Travel Required

Skills

Quants
Python
Analytics
Linear Algebra
statistics
time series

Job Details

Job Title: Quant Developer/ Analyst

Location: Jersey City, NJ/ Pittsburgh, PA Hybrid Role (3 days onsite role)

Contract/Full Time Both

Job Description:

  • Knowledge: Linear Algebra, statistics, and time series analysis
  • Technical: Proficient in Quants, Python, Analytics
  • Experience implementing analytics in risk/calc engine to generate valuation, return and 1st order risk measures.
  • Good understanding of equity and fixed income products, Exchange traded derivates, portfolio analysis, fund accounting, and NAV calculation.

Key Responsibilities:

  • Simulation and Analysis: Conducting simulations using specialized software to analyze product behavior under different conditions.
  • Performance Evaluation: Assessing factors like load capacity, stability, and material resilience based on simulation results.
  • Design Optimization: Identifying areas for improvement in product design by analyzing simulation data and suggesting modifications.
  • Report Generation: Preparing detailed reports, calculations, and technical justifications based on simulation results.
  • Collaboration: Working closely with other engineering disciplines (e.g., mechanical, civil, process) to integrate simulation results into the overall design process.
  • Compliance: Ensuring calculations and analyses adhere to relevant industry standards and codes.
  • Tools and Technologies:
  • Simulation Software: Often utilizes specialized software like CAESAR II, Pipestress, or similar tools for specific engineering domains.
  • CAD/CAE: May use computer-aided design (CAD) and computer-aided engineering (CAE) software for modeling and analysis.
  • Programming: May involve programming skills (e.g., Python) for scripting and automating calculations.
  • In essence, Calculation Engineers bridge the gap between theoretical design and practical application by using computational methods to predict and optimize the performance of engineered systems.
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