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Regression Analysis Jobs (NOW HIRING)

Texas Instruments Incorporated

$110 - $150/hr

Work with regression tools and develop scripts to submit cases for regression analysis * Analyze simulation results to ensure compliance with intended block-level behavior and system interactions

ClifyX

GEN AI Engineer

Irving, TX · On-site

$106K - $127K/yr

... regression analysis time series analysis and clustering. Qualifications : Required : • Strong Data Structures Any Language Code Comprehension Python or Java. • Ability to do hands on coding in ...

Texas Instruments

Design Verification Engineer

Dallas, TX · On-site

$120 - $180/hr

Work with regression tools and develop scripts to submit cases for regression analysis * Analyze simulation results to ensure compliance with intended block-level behavior and system interactions

ClifyX

Gen AI Engineer

Irving, TX · On-site

$106K - $127K/yr

... regression analysis time series analysis and clustering. Qualifications : Required : • Strong Data Structures Any Language Code Comprehension Python or Java. • Ability to do hands on coding in ...

DiCicco, Gulman & Company

Senior Analyst

Boston, MA · On-site

$95K - $126K/yr

... regression analysis Performing research on accounting and valuation standards and literature Conducting industry, market structure, and competitor-positioning studies Reviewing and summarizing ...

Ericsson GmbH

Si CAD CI CD Automation Engineer

Austin, TX · On-site

$120 - $150/hr

Apply AI/ML techniques to enhance engineering productivity, enable intelligent failure analysis, regression triage, and CI/CD pipeline optimization. * Build and maintain engineering dashboards ...

Systems Planning and Analysis

AFSIM Analyst

Quantico, VA · On-site

$100K - $120K/yr

This role supports engagement-level analysis through the development and execution of analytical models, statistical methods, parametric and non-parametric techniques, regression analysis, and ...

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Regression Analysis information

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How much do regression analysis jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for regression analysis in the United States is $32.41, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $37.02 per hour, depending on experience, location, and employer.

What is regression analysis?

A Regression Analysis job involves analyzing data to identify relationships between variables and make predictions. Professionals in this field use statistical techniques, such as linear and logistic regression, to interpret trends and patterns. They often work with large datasets, using tools like Python, R, or Excel to build models that support business decisions. These roles are common in industries like finance, healthcare, and marketing, where data-driven insights are crucial.

What are the typical responsibilities and challenges faced by professionals specializing in regression analysis?

Professionals in regression analysis are primarily responsible for collecting and cleaning data, selecting appropriate statistical models, running regression tests, and interpreting results for actionable insights. One of the key challenges in this role is ensuring the accuracy and validity of models when handling large, complex, or incomplete datasets, as well as communicating technical outcomes to non-technical stakeholders. These roles often involve close collaboration with data scientists, business analysts, and decision-makers to tailor analyses to specific organizational needs. By translating data patterns into understandable recommendations, regression analysts play a vital role in supporting company strategy and operational improvements.

What are the key skills and qualifications needed to thrive in regression analysis, and why are they important?

Excelling in Regression Analysis requires a solid background in statistics, mathematics, and data interpretation, typically supported by a degree in statistics, mathematics, data science, or a closely related field. Familiarity with analytical tools and programming languages such as R, Python, SAS, or SPSS, and knowledge of data visualization platforms are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills enable clear presentation of complex findings to diverse stakeholders. These competencies are vital for drawing reliable predictive insights, shaping data-driven business decisions, and collaborating seamlessly within multidisciplinary teams.

Is regression analysis a skill?

Regression analysis is considered a technical skill used in data analysis and statistical modeling. Proficiency typically involves understanding statistical concepts, using tools like Excel, R, or Python, and interpreting results accurately. It is often listed as a required skill in roles such as data analyst, data scientist, or quantitative analyst.

What jobs use regression analysis?

Regression analysis is used in a variety of jobs including data analysts, statisticians, financial analysts, marketing analysts, and research scientists. These roles involve analyzing data to identify trends, make predictions, and support decision-making, often using tools like Excel, R, or Python. Strong analytical skills and understanding of statistical methods are essential in these positions.
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Regression Analysis jobs near you
Infographic showing various Regression Analysis job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $67,422 per year, or $32.4 per hour.

AI Agent Developer QA Specialization

Accord Technologies Inc.

Warren, NJ • On-site

Contractor

Re-posted 25 days ago

Job description

AI Agent Developer – QA Specialization
Location: Warren, NJ
Position type: W2 contract
 

Job Summary

We are seeking a QA domain expert with strong experience in AI development to design and build advanced QA Agents. This role is ideal for a QA engineer/developer who has transitioned to AI/ML, Large Language Models (LLMs), and agentic architectures. You will be responsible for architecting, implementing, and optimizing AI agents that automate, augment, and scale quality assurance processes within our engineering teams.

Key Responsibilities

  • Analyze QA workflows to design agent architectures that automate requirement analysis, test generation, defect triage, and reporting.
  • Build, fine-tune, and maintain QA agents using frameworks such as LangChain, OpenAI, LlamaIndex, or custom RL approaches.
  • Engineer prompts and context strategies for LLM-powered test case generation, regression analysis, and intelligent reporting.
  • Integrate agents with code repositories, CI/CD systems, test management platforms, and communication tools.
  • Collaborate with QA, development, and AI/ML teams to collect requirements and continually improve agent performance.
  • Implement agent validation, test coverage measurement, and reliability evaluation for agent-driven QA flows.
  • Contribute to the continuous evolution of self-healing and adaptive QA agent features.
  • Document agent design, workflows, evaluation metrics, and operational guidelines.

Required Skills & Qualifications

  • Bachelor’s or Master’s in Computer Science, Engineering, or related field.
  • 3+ years in QA engineering, automation, or SDET roles.
  • 1+ years hands-on developing AI/LLM-based applications or agents (preferably for process automation or software quality).
  • Strong programming skills: Python (must); knowledge of JavaScript/TypeScript, Java, or Go is an advantage.
  • Proven experience with one or more of: LangChain, OpenAI API, LlamaIndex, Vertex AI, or similar agent and LLM frameworks.
  • Experience integrating AI solutions with DevOps toolchains (Jenkins, GitHub, Jira, etc.).
  • Deep understanding of software testing lifecycle, automation frameworks, and QA metrics.
  • Clear communication skills with an ability to document and explain agent logic and technical rationale.

Bonus/Preferred Skills

  • Experience designing agents for software quality–test generation, autonomous triage, or regression analysis.
  • Familiarity with RAG (Retrieval-Augmented Generation) and prompt tooling.
  • Knowledge of agent frameworks (e.g., CrewAI, AutoGen, or similar).
  • Contributions to open-source QA-AI tools or published research in autonomous QA.