

Data Migration Consultant
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Migration Consultant with a contract length of "unknown" and a pay rate of "unknown." Located in NYC (hybrid), it requires 5-10 years in data migration, proficiency in SQL and ETL tools, and a background in capital markets or Murex.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
-
ποΈ - Date discovered
August 6, 2025
π - Project duration
Unknown
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
New York, United States
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π§ - Skills detailed
#Matlab #Model Validation #Programming #R #Strategy #"ETL (Extract #Transform #Load)" #Migration #Python #SQL (Structured Query Language) #Data Migration #Data Quality #Documentation
Role description
Job Description:
Role: Data Migration Consultant/Quantitative Validation Expert
Location: NYC, NY/hybrid
Type: Contract
Data Migration Consultant
Responsibilities:
β’ Designs and executes data migration strategy from legacy systems to Murex.
β’ Handles ETL for trade data, static data (counterparties, books), and historical market data.
β’ Works with stakeholders to define mapping rules, transformation logic, and reconciliation methods.
Required Skills/Experience:
β’ 5β10 years in data migration projects (ideally in capital markets or Murex).
β’ Proficiency in SQL, ETL tools, and data quality frameworks.
β’ Strong understanding of trading data schemas and reference data.
Model Validation Analyst / Quantitative Validation Expert (2)
β’ Purpose: Validates front-office pricing models and risk analytics (e.g., PV, Greeks, XVA).
β’ Key Responsibilities:
β’ Independently verify the theoretical soundness and numerical accuracy of IRD/CRD pricing models implemented in Murex.
β’ Perform benchmark testing against in-house models, spreadsheets, or vendor tools.
β’ Review model documentation and work with quants/front office to ensure model transparency and regulatory alignment.
β’ Validate calibration techniques (e.g., yield curves, volatility surfaces, CDS spreads).
β’ Assist in model governance and sign-off process (may involve internal Model Risk Management (MRM) teams).
β’ Skills:
β’ Strong quantitative finance background (PhD/masterβs level preferred).
β’ Familiarity with Murex model architecture (or APIs if access is granted).
β’ Programming in Python, R, or MATLAB.
β’ Deep understanding of risk-neutral pricing, stochastic models, and numerical methods (e.g., Monte Carlo, PDEs).
Job Description:
Role: Data Migration Consultant/Quantitative Validation Expert
Location: NYC, NY/hybrid
Type: Contract
Data Migration Consultant
Responsibilities:
β’ Designs and executes data migration strategy from legacy systems to Murex.
β’ Handles ETL for trade data, static data (counterparties, books), and historical market data.
β’ Works with stakeholders to define mapping rules, transformation logic, and reconciliation methods.
Required Skills/Experience:
β’ 5β10 years in data migration projects (ideally in capital markets or Murex).
β’ Proficiency in SQL, ETL tools, and data quality frameworks.
β’ Strong understanding of trading data schemas and reference data.
Model Validation Analyst / Quantitative Validation Expert (2)
β’ Purpose: Validates front-office pricing models and risk analytics (e.g., PV, Greeks, XVA).
β’ Key Responsibilities:
β’ Independently verify the theoretical soundness and numerical accuracy of IRD/CRD pricing models implemented in Murex.
β’ Perform benchmark testing against in-house models, spreadsheets, or vendor tools.
β’ Review model documentation and work with quants/front office to ensure model transparency and regulatory alignment.
β’ Validate calibration techniques (e.g., yield curves, volatility surfaces, CDS spreads).
β’ Assist in model governance and sign-off process (may involve internal Model Risk Management (MRM) teams).
β’ Skills:
β’ Strong quantitative finance background (PhD/masterβs level preferred).
β’ Familiarity with Murex model architecture (or APIs if access is granted).
β’ Programming in Python, R, or MATLAB.
β’ Deep understanding of risk-neutral pricing, stochastic models, and numerical methods (e.g., Monte Carlo, PDEs).