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Regression Jobs (NOW HIRING)

10.1 Regression Client

Regression Oct 8

Hopkinton, MA · On-site

Job Responsibilities Conduct thorough regression testing to ensure software functionality remains intact after updates or changes. Execute black box testing to validate software performance against ...

Strong Tower Partners

Regression Tester

Orem, UT · On-site +1

$110K - $130K/yr

Job Summary As a Regression Tester, you will focus on end-to-end validation of the platform to ensure that existing functionality continues to work after updates, bug fixes, or new feature releases.

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How much do regression jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for regression in the United States is $51.44, according to ZipRecruiter salary data. Most workers in this role earn between $42.55 and $59.38 per hour, depending on experience, location, and employer.

What jobs pay 4000 a week without a degree?

High-paying jobs that can reach $4,000 a week without a degree often include roles such as experienced sales representatives, commercial pilots, real estate brokers, or skilled trades like electricians and plumbers. These positions typically require specialized skills, certifications, or extensive experience rather than formal college degrees.

What jobs use regression analysis?

Regression analysis is used in a variety of jobs such as data analysts, statisticians, financial analysts, marketing analysts, and data scientists. These roles involve building models to predict outcomes, identify trends, and support decision-making using statistical tools like Excel, R, or Python. Strong analytical skills and understanding of statistical concepts are essential for these positions.

What types of projects or problems does a Regression Analyst typically work on, and how do they collaborate with other teams?

A Regression Analyst typically works on projects involving trend analysis, forecasting, and identifying relationships between variables using statistical models. They often collaborate closely with data scientists, business analysts, and subject matter experts to interpret results and ensure models align with business objectives. Regular responsibilities include data cleaning, model development, and presenting findings to stakeholders. Successful collaboration and communication are key, as their insights frequently inform decision-making across departments such as marketing, finance, and operations.

What is a real life example of regression?

A regression analyst might use regression analysis to predict housing prices based on factors like size, location, and age of the property. This involves analyzing historical data to identify relationships between variables and make forecasts, often using statistical software such as R or Python. Such skills are essential for making data-driven decisions in finance, marketing, and other industries.

What is regression in the context of data analysis and statistics?

Regression is a statistical method used to examine the relationship between a dependent variable and one or more independent variables. It helps in predicting the value of the dependent variable based on the values of the independent variables. Common types include linear regression, which models a straight-line relationship, and logistic regression, which is used for predicting categorical outcomes. Regression analysis is widely used in fields such as economics, finance, biology, and machine learning to identify trends, make forecasts, and understand variable relationships.

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

To thrive as a Regression Analyst, you need a solid background in statistics, mathematics, and data analysis, typically supported by a relevant bachelor's or master's degree. Proficiency with statistical tools like R, Python, SAS, or SPSS, and experience with data visualization platforms are essential. Strong analytical thinking, attention to detail, and clear communication help in interpreting and presenting complex data findings. These skills are crucial for accurate modeling, data-driven decision-making, and effectively conveying actionable insights to stakeholders.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist or working in regression analysis. Many professionals transition into data science later in their careers by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Success depends on your skills, experience, and continuous learning rather than age.
More about Regression jobs
What cities are hiring for Regression jobs? Cities with the most Regression job openings:
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Regression jobs near you
Infographic showing various Regression job openings in the United States as of June 2026, with employment types broken down into 77% Full Time, 18% Part Time, and 5% Contract. Highlights an 71% Physical, 4% Hybrid, and 25% Remote job distribution, with an average salary of $106,997 per year, or $51.4 per hour.

Regression Oct 8

10.1 Regression Client

Hopkinton, MA • On-site

Other

Posted 28 days ago

Job description

Job Summary
We are seeking a detail-oriented individual with 1-3 years of experience in Quality Assurance (QA) to join our team in the Information Technology industry. The ideal candidate will possess a GED or High School Diploma and demonstrate proficiency in regression testing, black box testing, and smoke testing methodologies.
Job Responsibilities
Conduct thorough regression testing to ensure software functionality remains intact after updates or changes.
Execute black box testing to validate software performance against specified requirements without knowledge of internal code structure.
Perform smoke testing to verify that critical functionalities are working as intended before proceeding with further testing.
Collaborate with developers and other QA team members to identify and troubleshoot defects, ensuring timely resolution.
Document test cases, test results, and defects in a clear and concise manner to facilitate communication with stakeholders.
Participate in team meetings and contribute to continuous improvement initiatives within the QA process.
Knowledge
Strong understanding of QA methodologies and best practices, particularly in regression and black box testing.
Familiarity with various testing tools and software used in the QA process.
Ability to analyze and interpret complex requirements to develop effective test cases.
Excellent problem-solving skills and attention to detail to identify and document defects accurately.
Effective communication skills to collaborate with team members and report findings to management.
Basic knowledge of software development life cycle (SDLC) and agile methodologies is a plus.

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