Quantitative Analyst | Model Evaluation & Risk

Location: Remote / Hybrid Options | Work Mode: Full-time | Focus: Model Validation & Forecasting | Posting date/time : February 11, 2026

Job Description

Role Overview

The Quantitative Analyst (Quant) is responsible for developing, evaluating, and interpreting the quantitative models used for forecasting, optimization, and risk analysis. This role requires exceptional mathematical reasoning, a high level of comfort with structured datasets, and the ability to deconstruct complex model behaviors into clear, actionable explanations.

Key Responsibilities:

• Analyze model inputs, underlying assumptions, and statistical validity to ensure robust outputs.
• Evaluate predictive model performance and proactively identify unexpected or anomalous behaviors.
• Summarize complex quantitative findings into clear, structured formats for stakeholders.
• Validate data pipelines, feature sets, and transformation logic to maintain data integrity.
• Identify inconsistencies or areas requiring model recalibration.
• Support recurring evaluations of quantitative frameworks and simulation outputs.

Qualifications:

• Core Skills: Strong mathematical reasoning and analytical deconstruction.
• Data Proficiency: High comfort level working with and interpreting structured datasets.
• Communication: Ability to translate complex quantitative concepts into plain language.
• Nice-to-Have: Familiarity with Python, R, or specialized quantitative modeling libraries.

Job details made easy by trendtoday360

Position: Model Validation & Statistical Analyst
Focus: Forecasting Accuracy & Data Pipeline Integrity
Core Technology: Statistical Frameworks, Python/R (Preferred), Structured Data

✅ Job Summary and Focus:

This role is for a Mathematical Detective. While many quant roles focus solely on building models, this position places a heavy emphasis on Model Governance and Validation. The primary focus is Deconstruction—taking apart existing predictive models to see why they behave the way they do and ensuring their statistical validity remains intact over time. You will act as the “Quality Control” layer for the organization’s forecasting engine, ensuring that data pipelines are clean and that simulations are not just mathematically sound, but logically grounded.

📌 Key ATS Resume Keywords:

Quantitative Analyst, Quant, Model Validation, Statistical Validity, Forecasting, Risk Analysis, Data Pipelines, Feature Sets, Predictive Modeling, Recalibration, Python, R, Structured Data, Simulation, Mathematical Reasoning, Anomaly Detection.

💰 Industry and Demographic Insights:

The demand for Model Validation Specialists has surged in 2026 as organizations increase their reliance on automated forecasting and AI-driven decision-making.

• Market Trends: In 2026, firms are prioritizing “Explainable Quant” roles. Analysts who can not only run a model but also explain its logic to senior leadership command a 12-15% salary premium.
• Racial Representation in U.S. Quantitative Analysis: Based on 2025 industry labor data for “Financial and Data Quantitative Analysts”:
  • White: 46.5%
  • Asian: 39.8%
  • Hispanic or Latino: 6.4%
  • Black or African American: 5.1%
  • Other/Multiracial: 2.2%
• Gender in Quantitative Finance: Women currently represent approximately 21% of the quantitative analyst workforce. Many firms are now offering highly flexible Remote/Hybrid models specifically to attract diverse, top-tier talent in this competitive niche.
• The Python/R Shift: While traditional Excel-based modeling remains, 92% of top-performing quants in 2026 utilize Python or R to handle the scale of modern structured datasets.

job updates by trendtoday360.