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Quant Jobs in Ohio (NOW HIRING)

US Bank

Quantitative Model Analyst - AML

Cincinnati, OH · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The person in this role will join a team of Financial Intelligence Unit (FIU) quantitative analysts responsible for the ongoing monitoring, testing, analytical review, and governance of AML ...

US Bank

Quantitative Model Analyst - AML

Columbus, OH

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The person in this role will join a team of Financial Intelligence Unit (FIU) quantitative analysts responsible for the ongoing monitoring, testing, analytical review, and governance of AML ...

The Scotts Miracle Gro Company

Quantitative Analyst

Columbus, OH · On-site

$77K - $90K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

The Quantitative Analyst will manage and support high-impact research projects, primarily focusing on survey design, consumer data analysis, and the synthesis of quantitative data to inform key ...

US Bank

Quantitative Model Analyst - Treasury

Cincinnati, OH

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Corporate Treasury's Asset & Liability Management Quantitative Finance group supports these efforts by developing quantitative models and methods that link the Bank's balance sheet to the broader ...

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Showing results 21-40

All JobsQuant JobsQuant Jobs in Ohio

Quant information

See Ohio salary details

$93.2K

$161.4K

$246.7K

How much do quant jobs pay per year?

As of Aug 14, 2026, the average yearly pay for quant in Ohio is $161,360.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,900.00 and $189,200.00 per year, depending on experience, location, and employer.

What does a quant do?

Quant refers to a quantitative analyst whose responsibilities are to research and analyze market trends in finance. As a quant, you research and decipher statistics and design financial models to help banks, insurance companies, and other finance-focused organizations assess and prevent their risk, make sound investments, and better understand pricing structures to increase profit. Your duties also include creating codes for programs that follow financial trends and patterns, recording data and analyses, and consulting with business leaders in an organization to offer suggestions to combat potential financial risks. Large financial institutions and firms with trading processes typically hire quants.

What is a quant?

Quants, short for quantitative analysts, are professionals who use mathematical models, statistics, and computational techniques to analyze financial data and develop trading strategies. They are typically employed by investment banks, hedge funds, asset management firms, and financial technology companies. Quants play a crucial role in pricing securities, managing risk, and optimizing portfolios. Their expertise is essential for making data-driven decisions in complex financial markets.

What are some common challenges faced by quants when collaborating with software developers and traders?

Quants often encounter challenges in bridging the gap between theoretical models and practical implementation. Effective communication is essential, as translating complex quantitative concepts into actionable trading strategies requires close collaboration with both software developers and traders. Misunderstandings can occur due to differences in technical language or priorities, so fostering a collaborative environment and being open to feedback is crucial. Regular meetings and clear documentation can help ensure that models are accurately implemented and aligned with trading objectives.

What are the key skills and qualifications needed to thrive as a quant, and why are they important?

To thrive as a Quant, you need strong quantitative and analytical skills, typically supported by advanced degrees in mathematics, statistics, physics, or related fields. Proficiency with programming languages like Python or C++, financial modeling, and familiarity with tools such as MATLAB or R are essential, along with knowledge of financial markets. Exceptional problem-solving, attention to detail, and effective communication help Quants stand out in collaborative and high-stakes environments. These skills enable Quants to develop robust models and strategies that drive critical decision-making and risk management in finance.

What is the difference between Quant vs Data Analyst?

AspectQuantData Analyst
Required CredentialsDegree in Math, Finance, or Computer Science; often requires advanced degreesBachelor's in Statistics, Economics, or related field; sometimes requires certifications
Work EnvironmentFinancial firms, hedge funds, investment banksCorporations, consulting firms, market research
Employer & Industry UsagePrimarily in finance and tradingAcross various industries including finance, marketing, healthcare
Common Search & Comparison IntentUnderstanding quantitative roles in financeExploring data analysis careers

While both Quant and Data Analyst roles involve working with data, Quants focus on developing complex models for trading and risk management in finance, often requiring advanced degrees and specialized skills. Data Analysts typically interpret data to inform business decisions across industries, with a broader scope and different tools. The roles overlap in data handling but differ significantly in application and industry focus.

Do quants get paid well?

Quantitative analysts, or quants, typically earn high salaries due to their specialized skills in mathematics, programming, and finance. Compensation often includes base pay, bonuses, and profit-sharing, reflecting the demand for their expertise in trading, risk management, and financial modeling.
More about Quant jobs

What are the most commonly searched types of Quant jobs in Ohio?

The most popular types of Quant jobs in Ohio are:

What are popular job titles related to Quant jobs in Ohio?

For Quant jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Quant jobs in Ohio look for?

The top searched job categories for Quant jobs in Ohio are:

Quant jobs near you
Infographic showing various Quant job openings in Ohio as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 46% In-person, and 54% Remote job distribution, with an average salary of $161,360 per year, or $77.6 per hour.

Quantitative Analyst

Wright-Patt Credit Union

Beavercreek, OH

Full-time

Posted 22 days ago

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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