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Weekend Quantitative Analyst Jobs in Ohio (NOW HIRING)

The Scotts Company LLC

Quantitative Analyst

Columbus, OH · On-site

$77K - $90K/yr

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 ...

Northwest

Quantitative Analyst II

Independence, OH · On-site

IN0534 Fishers, OH0523 Independence Bus Office, OH0713 NW Bancshares HQ, PA0258 Bellevue The Quantitative Analyst II is responsible for supporting developing and maintaining complex financial models ...

Northwest

Quantitative Analyst II

Columbus, OH · On-site

IN0534 Fishers, OH0523 Independence Bus Office, OH0713 NW Bancshares HQ, PA0258 Bellevue The Quantitative Analyst II is responsible for supporting developing and maintaining complex financial models ...

US Bank

Quantitative Model Analyst 2

Cincinnati, OH

Our team is seeking a strong, decisive, results-oriented quantitative analyst who will be responsible for building complex statistical models for our income statement. The model-building process is ...

US Bank

Quantitative Model Analyst 3 - AML

Columbus, OH · On-site

Experience working with quantitative models, analytics, or monitoring frameworks in a regulated environment * Proficiency in SAS, SQL, and Python for data analysis, testing, and automation * Strong ...

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Weekend Quantitative Analyst information

See Ohio salary details

$53.7K

$127.3K

$228.2K

How much do weekend quantitative analyst jobs pay per year?

As of Jul 27, 2026, the average yearly pay for weekend quantitative analyst in Ohio is $127,277.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $138,300.00 per year, depending on experience, location, and employer.

What are the typical responsibilities of a Weekend Quantitative Analyst, and how does the work differ from weekday roles?

As a Weekend Quantitative Analyst, your main responsibilities typically include real-time data analysis, monitoring market movements, and supporting trading teams during weekend trading sessions. Unlike weekday roles that may focus more on research or strategy development, weekend analysts often prioritize immediate problem-solving and rapid response to market events. Collaboration is usually remote, with communication channels open to traders and risk managers who require timely insights. This role is ideal for individuals seeking flexibility while still contributing to critical decision-making processes in financial institutions.

What is a Weekend Quantitative Analyst?

A Weekend Quantitative Analyst is a professional who applies mathematical and statistical techniques to analyze data and solve financial or business problems, specifically during weekends. They often work for financial institutions, investment firms, or consulting companies, focusing on tasks such as modeling, risk analysis, and data interpretation. This role may involve supporting trading activities, conducting research, or testing algorithms outside of regular weekday hours. Weekend Quantitative Analysts help organizations maintain continuous operations and respond to market changes that occur over weekends. Strong skills in mathematics, programming, and data analysis are essential for success in this position.

What is the difference between Weekend Quantitative Analyst vs Part-Time Quantitative Analyst?

AspectWeekend Quantitative AnalystPart-Time Quantitative Analyst
CredentialsTypically requires a degree in finance, mathematics, or related field; certifications like CFA are commonSimilar educational background; certifications optional but beneficial
Work EnvironmentUsually works during weekends or specific days, often in financial firms or hedge fundsFlexible hours, often in the same environments as weekend analysts
Employer & Industry UsageUsed by hedge funds, asset managers, and financial institutions for weekend analysisCommon across financial firms for flexible, part-time support roles

The main difference between a Weekend Quantitative Analyst and a Part-Time Quantitative Analyst lies in their work schedule. Weekend analysts specifically work during weekends, while part-time analysts may have flexible hours throughout the week. Both roles require similar skills and credentials, and are used in comparable financial environments to support quantitative research and analysis.

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

To thrive as a Weekend Quantitative Analyst, you need strong quantitative analysis skills, proficiency in statistics, and a degree in mathematics, finance, or a related field. Familiarity with programming languages like Python or R, statistical modeling tools, and data visualization platforms is typically required. Exceptional problem-solving abilities, attention to detail, and effective time management set top performers apart in this role. These skills and qualities are crucial for accurate data-driven insights and timely financial decision-making, especially during critical weekend market hours.
What are the most commonly searched types of Quantitative Analyst jobs in Ohio? The most popular types of Quantitative Analyst jobs in Ohio are:
What are popular job titles related to Weekend Quantitative Analyst jobs in Ohio? For Weekend Quantitative Analyst jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Weekend Quantitative Analyst jobs in Ohio look for? The top searched job categories for Weekend Quantitative Analyst jobs in Ohio are:
Weekend Quantitative Analyst jobs near you
Quantitative Analyst

Quantitative Analyst

Wright-Patt Credit Union

Beavercreek, OH

Full-time

Posted 4 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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