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Math Software Engineer Jobs in Georgia (NOW HIRING)

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Math Software Engineer information

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

To thrive as a Math Software Engineer, you need a strong background in mathematics, computer science, and algorithm development, typically supported by a relevant degree. Proficiency in programming languages such as Python, C++, or MATLAB, along with experience using mathematical libraries and tools like NumPy or SciPy, is essential. Analytical thinking, problem-solving, and effective collaboration are valuable soft skills that enhance performance in this role. These skills ensure the development of robust, efficient, and accurate mathematical software solutions that meet complex computational requirements.

How do Math Software Engineers typically collaborate with other teams during the development process?

Math Software Engineers often work closely with cross-functional teams, such as data scientists, product managers, and front-end developers, to ensure mathematical models and algorithms are accurately implemented in software products. Collaboration involves regular meetings to discuss requirements, problem-solving sessions to address computational challenges, and code reviews for maintaining mathematical integrity. Communicating complex mathematical concepts in an accessible way is a key part of the role, enabling teams to create robust and efficient solutions that meet user needs.

What are Math Software Engineers?

Math Software Engineers are professionals who design, develop, and optimize software that performs complex mathematical computations. They often work on algorithms, numerical analysis, and simulation tools used in scientific research, finance, engineering, or data analysis. Their work ensures that mathematical models and computations are both accurate and efficient within various applications. Math Software Engineers typically have a strong background in mathematics, computer science, and programming languages such as Python, C++, or MATLAB.

What is the difference between Math Software Engineer vs Data Scientist?

AspectMath Software EngineerData Scientist
Required CredentialsBachelor's or higher in Computer Science, Mathematics, or related fieldsBachelor's or higher in Statistics, Data Science, or related fields
Work EnvironmentSoftware development teams, R&D labs, tech companiesData analysis teams, research departments, tech firms
Industry UsageDeveloping algorithms, modeling, simulationData analysis, predictive modeling, insights generation

Math Software Engineers focus on developing mathematical algorithms and software solutions, often working on simulations and modeling. Data Scientists analyze data to extract insights and build predictive models. While both roles require strong math skills, Math Software Engineers are more involved in software development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Math Software Engineer jobs in Georgia? The most popular types of Math Software Engineer jobs in Georgia are:
What cities in Georgia are hiring for Math Software Engineer jobs? Cities in Georgia with the most Math Software Engineer job openings:
Associate Product Software Engineer - Systems Engineer in Test

Associate Product Software Engineer - Systems Engineer in Test

Wolters Kluwer

Kennesaw, GA • On-site

Full-time

Posted 29 days ago


Wolters Kluwer rating

8.8

Company rating: 8.8 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

32nd of 188 rated software companies


Job description

Job Summary:
Wolters Kluwer is seeking an Associate Product Software Engineer to join their innovative team. The role focuses on developing and maintaining automated testing solutions and integrating them into CI/CD pipelines to enhance software quality and delivery confidence.
Responsibilities:
• Learning, implementation, and execution of well‑defined tasks are central to this position under appropriate technical guidance. Autonomy and responsibility are expected to increase over time as skills, experience, and familiarity grow within our application domains, with growth supported through mentorship, review, and established engineering practices.
• Automated Test Development: Assist in designing, coding, and maintaining automated unit, integration, functional, smoke, regression, and load tests.
• Test Integration: Support the integration of automated tests into continuous integration and continuous delivery (CI/CD) pipelines to ensure automated validation from pull request through deployment.
• Test Code Engineering: Write and maintain test code that follows established coding standards, patterns, and best practices, treating test software as production‑quality code.
• Defect Detection and Analysis: Identify, log, and assist in analyzing software defects surfaced through automated test results, logs, and metrics.
• Collaboration Across Teams: Work collaboratively with software engineers, quality assurance engineers, DevOps engineers, and load test engineers to support an automated, end‑to‑end SDLC.
• Shift‑Left Testing Support: Assist in developing and maintaining testing assets alongside feature development to ensure testing occurs early in the development lifecycle.
• Version Control and Code Review: Use source control systems to manage test code changes and participate in code reviews to ensure correctness and maintainability.
• Debugging and Troubleshooting: Aid in debugging test failures, automation issues, pipeline problems, and environment‑related failures.
• Requirements and System Understanding: Develop an understanding of application behavior, system requirements, and non‑functional expectations such as performance, availability, and reliability.
• Quality Metrics and Coverage: Support efforts to improve test coverage, execution reliability, and confidence metrics across a large application portfolio.
• Learning and Skill Development: Continuously learn automated testing methodologies, tools, frameworks, CI/CD practices, and AI‑assisted development techniques supported by the organization.
Qualifications:
Required:
• Learning, implementation, and execution of well‑defined tasks are central to this position under appropriate technical guidance.
• Autonomy and responsibility are expected to increase over time as skills, experience, and familiarity grow within our application domains.
• Automated Test Development: Assist in designing, coding, and maintaining automated unit, integration, functional, smoke, regression, and load tests.
• Test Integration: Support the integration of automated tests into continuous integration and continuous delivery (CI/CD) pipelines to ensure automated validation from pull request through deployment.
• Test Code Engineering: Write and maintain test code that follows established coding standards, patterns, and best practices, treating test software as production‑quality code.
• Defect Detection and Analysis: Identify, log, and assist in analyzing software defects surfaced through automated test results, logs, and metrics.
• Collaboration Across Teams: Work collaboratively with software engineers, quality assurance engineers, DevOps engineers, and load test engineers to support an automated, end‑to‑end SDLC.
• Shift‑Left Testing Support: Assist in developing and maintaining testing assets alongside feature development to ensure testing occurs early in the development lifecycle.
• Version Control and Code Review: Use source control systems to manage test code changes and participate in code reviews to ensure correctness and maintainability.
• Debugging and Troubleshooting: Aid in debugging test failures, automation issues, pipeline problems, and environment‑related failures.
• Requirements and System Understanding: Develop an understanding of application behavior, system requirements, and non‑functional expectations such as performance, availability, and reliability.
• Quality Metrics and Coverage: Support efforts to improve test coverage, execution reliability, and confidence metrics across a large application portfolio.
• Learning and Skill Development: Continuously learn automated testing methodologies, tools, frameworks, CI/CD practices, and AI‑assisted development techniques supported by the organization.
• Software Engineering: The ability to design, develop, and maintain software systems and applications by applying principles and techniques of computer science, engineering, and mathematical analysis.
• Software Development: The ability to design, write, test, and implement software programs, applications, and systems, including familiarity with programming languages, software architecture, and testing approaches.
• Programming: The ability to design, write, test, debug, and maintain code using languages such as Python, Java, or C++.
• Problem Solving: The ability to analyze complex problems, identify possible approaches, and implement effective solutions.
• Analysis: The ability to break down complex systems or issues and understand how components interact.
• Testing: The ability to evaluate software systems and processes to identify defects and ensure quality and functionality.
• Agile: Familiarity with agile principles emphasizing adaptability, continuous improvement, and iterative delivery.
• Source Code Repository: The ability to use source code repositories to manage changes, collaborate with others, and participate in branching and merging workflows.
• Relational Database: The ability to work with relational databases, including basic SQL usage and understanding of data relationships.
• Advanced Technology Adoption and Utilization: AI Tool Proficiency for basic coding, debugging, and documentation.
• AI Output Validation to verify correctness and functionality.
• Responsible AI Usage in accordance with organizational guidelines.
• Basic Agent Usage for routine development and automation tasks.
• Analytical Skills
• Inclusive Collaboration
• Drive to Perform
• Accountability
• Functional Expertise
• Operational Expertise
Company:
Wolters Kluwer is an information services company specializing in software solutions and services for the healthcare and legal sectors. Founded in 1836, the company is headquartered in Alphen Aan Den Rijn, NLD, with a team of 10001+ employees. The company is currently Late Stage.

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