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Cross Asset Quantitative Analyst Jobs (NOW HIRING)

Franklin Templeton Investments

NY · On-site

Fiduciary Trust International is owned by Franklin Templeton, a dynamic firm that spans asset ... Senior Quantitative Analyst, Quantitative & Risk Analytics The Quantitative and Risk Analytics ...

Franklin Templeton Investments

Fiduciary Trust International is owned by Franklin Templeton, a dynamic firm that spans asset ... Senior Quantitative Analyst, Quantitative & Risk Analytics The Quantitative and Risk Analytics ...

Fanatics Inc

Quantitative Analyst I

Denver, CO · On-site

$100K - $115K/yr

As a Quantitative Analyst, you'll operate at the intersection of sports trading, mathematics, and ... assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an ...

New

ENGIE Group

Quantitative Analyst II_TRQA1H

Houston, TX · On-site

$77K - $118K/yr

Within SEM, the Asset Backed Trading (ABT) group is responsible for pricing and managing risks ... As a Quantitative Analyst II, you will help maximize the value of ENGIE's portfolio of renewable ...

Aplaro Ltd

Quantitative Analyst

Manhattan, NY · On-site

$142K - $213K/yr

The Quantitative Analyst is a strategic professional who stays abreast of developments within own ... assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy ...

Capital One Group

As a Quantitative Analyst at Capital One, you'll be part of a team that's leading the next wave of ... Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.

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Cross Asset Quantitative Analyst information

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$40K

$88.4K

$155K

How much do cross asset quantitative analyst jobs pay per year?

As of Sep 10, 2026, the average yearly pay for cross asset quantitative analyst in the United States is $88,429.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $101,000.00 per year, depending on experience, location, and employer.

What are popular job titles related to Cross Asset Quantitative Analyst jobs?

For Cross Asset Quantitative Analyst jobs, the most frequently searched job titles are:

Infographic showing various Cross Asset Quantitative Analyst job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $88,429 per year, or $42.5 per hour.

Quantitative Analyst

Beavercreek, OH • On-site

Wright-Patt Credit Union
Finance and Insurance • 1 - 5K employees
Learn more about Wright-Patt Credit Unionexternal

Full-time

This job post has expired today. Applications are no longer accepted.

Wright-Patt Credit Union rating

5.8

Company rating: 5.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Job description

The Quantitative Analyst is responsible for leading high-impact statistical analysis, measurement design, and scalable analytics solutions that improve business performance and decision-making. This role partners closely with Strategy, Product, and Technology teams to evaluate key initiatives, identify performance drivers, develop statistically sound measurement approaches, and deliver executive-ready insights that influence priorities and investments. The Quantitative Analyst combines strong analytical depth with automation and repeatability, ensuring insights are accurate, timely, and operationally useful.

1)      High-Impact Quantitative Analysis & Decision Science (30%): Use statistical methods to identify drivers of performance, validate hypotheses, and quantify the impact of business decision using structured and repeatable approaches.

a)       Perform exploratory data analysis, segmentation, and trend analysis to uncover patterns and anomalies.

b)      Apply statistical techniques such as hypothesis testing, confidence intervals, correlation, and regression analysis.

c)       Identify opportunities for growth, efficiency, and experience improvement using data-backed recommendations.

d)      Deliver decision-ready outputs that connect analysis to actions, tradeoffs, and expected outcomes.

2)      Experimentation, Testing, and Impact Evaluation (25%): Design measurement frameworks that ensure the organization can track initiative performance, quantify impact, and drive accountability.

a)       Support A/B testing and experiment analysis including test design inputs, lift measurement, and interpretation.

b)      Partner with product and business teams to define success metrics, baselines, and measurement plans.

c)       Evaluate initiative effectiveness using controlled comparisons, pre/post analysis, and statistical significance testing.

d)      Develop standardized experiment readouts and decision frameworks to improve speed and consistency.

3)      Predictive Analytics & Optimization (20%): Drive advanced analytics efforts that improve targeting, prioritization, and decision-making through modeling and quantitative scoring.

a)       Partner with data scientists to support model development by preparing datasets, validating features, and interpreting outputs.

b)      Build and maintain scoring frameworks (propensity, prioritization, classification support) aligned to business use cases.

c)       Support model evaluation using practical performance measures (lift, precision/recall, error rates).

d)      Translate model outputs into actionable recommendations and operational workflows.

4)      Automation & Scalable Analytics Delivery (15%): Increase speed, consistency, and reliability of insights by automating analysis workflows and enabling scalable analytics delivery.

a)       Develop automated analysis workflows using SQL and Python to reduce manual effort.

b)      Build reusable scripts, templates, and standardized datasets to improve reliability and consistency.

c)       Partner with data engineering teams to improve data availability and support repeatable pipelines.

d)      Implement monitoring and alerting for key performance indicators and threshold-based changes.

5)      Communication, Visualization, and Executive Enablement (10%): Present actionable insights to senior leadership in a format that is relevant for the audience.

a)       Build clear, executive-ready summaries and visualizations tied to business outcomes.

b)      Present findings and recommendations to senior leaders and cross-functional teams.

c)       Communicate confidence levels, limitations, and tradeoffs in a practical way.

d)      Ensures proper policies, procedures, risk mitigation activities, and operating controls are followed. Reports gaps in policies, procedures, and operating controls to leadership to ensure member impact and risk is mitigated.  

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