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Quantitative Analyst Jobs in Springfield, OH (NOW HIRING)

Perform extensive quantitative analysis, including analysis of cash flow. * Prepare draft cost analyses and price reasonableness assessments. * Provide analysis and guidance to program offices to ...

Perform extensive quantitative analysis, including analysis of cash flow. * Prepare draft cost analyses and price reasonableness assessments. * Provide analysis and guidance to program offices to ...

Perform extensive quantitative analysis, including analysis of cash flow. * Prepare draft cost analyses and price reasonableness assessments. * Provide analysis and guidance to program offices to ...

Senior Analyst*

Dayton, OH · On-site

$82K - $108K/yr

Public Health (with quantitative emphasis) * Mathematics * or a closely related quantitative discipline * Minimum 5 years of experience performing statistical analyses in a healthcare, public health ...

Senior Analyst*

Dayton, OH · On-site

$82K - $108K/yr

Public Health (with quantitative emphasis) * Mathematics * or a closely related quantitative discipline * Minimum 5 years of experience performing statistical analyses in a healthcare, public health ...

Strong quantitative analysis capabilities * Demonstrated knowledge of Agile methodology. * Demonstrated knowledge of project management discipline. * Strong organizational skills. * Technical ...

Business Analyst

Beavercreek, OH · On-site

$100K - $140K/yr

Strong quantitative analysis capabilities Demonstrated knowledge of Agile methodology. Demonstrated knowledge of project management discipline. Strong organizational skills. Technical document ...

Perform quantitative analyses supporting program evaluation related to human performance, operational readiness, force health protection, and organizational effectiveness. * Develop, test, and refine ...

Senior Analyst* (26.29)

Dayton, OH

$83K - $110K/yr

Public Health (with quantitative emphasis) * Mathematics * or a closely related quantitative discipline * Minimum 5 years of experience performing statistical analyses in a healthcare, public health ...

Senior Analyst* (26.29)

Dayton, OH · On-site

$83K - $110K/yr

Public Health (with quantitative emphasis) * Mathematics * or a closely related quantitative discipline * Minimum 5 years of experience performing statistical analyses in a healthcare, public health ...

Perform quantitative analyses supporting program evaluation related to human performance, operational readiness, force health protection, and organizational effectiveness. * Develop, test, and refine ...

Perform quantitative analyses supporting program evaluation related to human performance, operational readiness, force health protection, and organizational effectiveness. * Develop, test, and refine ...

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Quantitative Analyst information

See Springfield, OH salary details

$50.9K

$120.6K

$216.2K

How much do quantitative analyst jobs pay per year?

As of Jul 29, 2026, the average yearly pay for quantitative analyst in Springfield, OH is $120,589.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $131,100.00 per year, depending on experience, location, and employer.

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

To thrive as a Quantitative Analyst, you need a strong background in mathematics, statistics, computer science, and finance, often supported by an advanced degree such as a master's or PhD. Expertise in programming languages like Python, R, or MATLAB, as well as familiarity with financial modeling tools and statistical software, is typically required. Analytical thinking, problem-solving abilities, and clear communication skills help you interpret complex data and convey insights to stakeholders. These competencies are crucial for developing accurate financial models, managing risk, and enabling data-driven decision-making in competitive financial environments.

What Does a Quantitative Analyst Do?

The responsibilities of quantitative analysts, or quants, include using mathematical models and statistics to analyze data to assess risks and develop solutions for business issues. In this role, you can work in a variety of industries, from production to finance to insurance. You typically gather and interpret data to help an organization implement a solution for maintaining its fiscal health. Duties vary with the industry. Some positions focus on collecting information from the general public or consumers of particular products through the use of polls and surveys to improve their design and marketing. Other quants work alongside researchers in the health care field to test treatments and medical equipment design.

Is a quant analyst high paying?

Quantitative analysts typically earn high salaries due to their specialized skills in mathematics, programming, and finance. Compensation often includes base salary, bonuses, and profit-sharing, especially in financial firms and hedge funds. Experience, education, and technical proficiency influence earning potential significantly.

How does a Quantitative Analyst typically collaborate with other departments within a financial organization?

Quantitative Analysts frequently work closely with traders, portfolio managers, risk managers, and IT professionals to develop, test, and implement financial models. Effective communication is essential, as they must translate complex quantitative findings into actionable insights for decision-makers. It's common to participate in cross-functional meetings, provide model validation support, and help interpret results for non-technical stakeholders. This collaborative environment fosters both technical skill development and a deeper understanding of the business, which can open doors to broader career opportunities.

What are Quantitative Analysts?

Quantitative Analysts, often called 'quants,' are professionals who use mathematical models, statistics, and computer programming to analyze financial data and support decision-making in finance. They develop and implement complex models to assess risk, value financial securities, and identify profitable investment opportunities. Quants are commonly employed by investment banks, hedge funds, asset management companies, and other financial institutions. Their work helps optimize trading strategies, manage risk, and improve financial performance.

Do JP Morgan hire quants?

JP Morgan hires quantitative analysts, often called quants, to develop models for trading, risk management, and investment strategies. Candidates typically need strong backgrounds in mathematics, programming, and finance, with skills in tools like Python, R, or MATLAB. The firm offers roles across various divisions, including investment banking and asset management.

What do you do as a quantitative analyst?

A quantitative analyst, or quant, develops mathematical models to analyze financial data and inform investment decisions. They use programming languages like Python or R, and tools such as Excel and statistical software, to identify trends, assess risks, and optimize portfolios in finance or trading environments.

What is the difference between Quantitative Analyst vs Data Scientist?

AspectQuantitative AnalystData Scientist
Required CredentialsDegree in finance, mathematics, or statistics; often certifications like CFADegree in computer science, statistics, or related fields; certifications like CAP or data science certifications
Work EnvironmentFinancial firms, investment banks, hedge fundsTech companies, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in finance and investment sectorsAcross multiple industries including tech, healthcare, and retail
Common Search & Comparison IntentUnderstanding roles in finance and investment analysisExploring data analysis and machine learning roles

While both roles involve data analysis and statistical skills, Quantitative Analysts focus on financial modeling and investment strategies within finance firms. Data Scientists have a broader scope, applying data analysis across various industries, often with programming and machine learning expertise.

Will AI replace quant analysts?

AI is transforming quantitative analysis by automating data processing and modeling tasks, but it is unlikely to fully replace quant analysts. Instead, AI tools are expected to augment their work, requiring analysts to develop skills in programming, machine learning, and data interpretation to stay relevant in the evolving field.
What are popular job titles related to Quantitative Analyst jobs in Springfield, OH? For Quantitative Analyst jobs in Springfield, OH, the most frequently searched job titles are:
What cities near Springfield, OH are hiring for Quantitative Analyst jobs? Cities near Springfield, OH with the most Quantitative Analyst job openings:
Infographic showing various Quantitative Analyst job openings in Springfield, OH as of July 2026, with employment types broken down into 81% Full Time, 12% Part Time, and 7% Contract. Highlights an 84% In-person, 3% Hybrid, and 13% Remote job distribution, with an average salary of $120,589 per year, or $58 per hour.

Full-time

Posted 6 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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