Quantitative Analytics Lead

4 weeks ago

London, Greater London, United Kingdom Enfusion Full time
Job Description

Enfusion is a pioneer in developing innovative, native cloud investment management software, analytics, and managed services for asset managers and hedge funds around the globe. We underpin the investment operations of fund managers from our global offices spanning four continents. Our unique, seamless, SaaS-based platform is reshaping the global investment operations landscape by removing traditional information boundaries and uniting the front-, middle- and back-office into one system, with one unified data set.

We are seeking a hands-on Quantitative Analytics Lead to spearhead the development and implementation of sophisticated models and methodologies aimed at the quantification of risk and measuring performance. This position will play a critical role in the delivery of first-class risk services to our clients including cross-asset flexible, customizable tools and models that illustrate valuation transparency.

Key Responsibilities
  • Participate in all aspects of the model life cycle, including design, implementation, testing, production, validation, and performance monitoring.
  • Analyze our quantitative library and systems to identify performance inefficiencies and scaling opportunities.
  • Interact with production clients on queries including price challenges, model/data validation requests, workflow testing, etc.
  • Work with the sales team in new client engagements, often involving in-person client visits as well as conducting in-depth product testing and coverage checks/validation
  • Work with the support teams to answer complicated questions related to risk, performance, and valuation.
  • Act as an SME, collaborating with internal stakeholders, including engineers and product owners to drive new enhancements in our valuation/data platform, and understand technical requirements to implement high performance code enhancing analytics infrastructure.
Requirements
  • Masters or Ph.D. degree in a quantitative field such as statistics, applied mathematics, economics, quantitative finance, and operations research.
  • Strong quantitative skills and deep understanding of the following technical areas: 1) financial mathematics (e.g., derivatives pricing models, stochastic calculus, advanced linear algebra); 2) econometrics (e.g., time series analysis, copulas, etc.) and machine learning techniques; and 3) numerical methods and optimization (e.g., Monte Carlo simulation and finite difference techniques).
  • 10+ years of direct work experience in financial risk modeling, risk measurement and management, and regulatory capital requirements.
  • Hands-on experience in the entire model development lifecycle including research, implementation, ongoing monitoring, and production maintenance.
  • Experience in writing, editing, or reviewing technical documents suitable for regulatory or banking context.

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