Software Reliability
hace 2 semanas
There are 7 billion people on this planet. And by 2050, there will be 2 billion more... many moving into urban centers at an unprecedented rate. Making sure there is enough food, fiber and infrastructure for our rapidly growing world is what we’re all about at John Deere. And it’s why we’re investing in our people and our technology like never before in our 175-year history. Here the world’s brightest minds are tackling the world’s biggest challenges. If you believe one person can make the world a better place, we’ll put you to work. RIGHT NOW.
Title: Software Reliability
Primary Location: Garza Garcia
Function: Data & Analytics (CA)
John Deere is a foremost leader in the ag equipment business, and we continue to put a solid stamp on other industries. For over 150 years, the company’s portfolio of groundbreaking products has grown to include industries related to and outside of agriculture, including Turf, Construction and Forestry and Wind Technologies. The image of John Deere is no longer that of a signature green tractor meandering across a field; it’s been replaced with an image of acceleration, swift progress, and innovative leaping toward the company’s 200th year. The product line alone serves as proof with advances in machine performance, equipment automation, fleet management, and John Deere’s ongoing investment in emerging markets.
**Main Responsabilities**:
- Collaborate with embedded software development teams to understand software architecture, design, and implementation processes.
- Design and implement code-based metrics to evaluate software reliability and performance.
- Analyze existing codebases to identify patterns and areas for improvement related to reliability.
- Develop new tools and methods while identifying improvement opportunities for existing tools and processes.
- Work alongside competency leaders, product owners, and IT scrum teams to deliver analytical solutions.
- Create and refine defect prediction models using historical test data and software metrics.
- Utilize statistical analysis and machine learning techniques to forecast potential defects and reliability issues.
- Generate comprehensive reports and dashboards to communicate findings and recommendations to stakeholders.
- Stay current with industry trends in software reliability engineering and data analysis.
- Develop training materials and conduct sessions to enhance team capabilities regarding reliability metrics and defect prediction techniques.
- Maintain clear documentation of processes, methodologies, and findings related to software reliability metrics and models.
- Facilitate knowledge sharing and best practices among software teams to enhance reliability metrics.
**What skills you need**:
- Strong analytical skills with experience in statistical analysis, machine learning, and data visualization.
- Proficient in Python, SQL, GitHub, and Tableau.
- Excellent communication and collaboration skills.
**What makes you stand out**:
- 2-3 years of experience in software development, particularly with embedded software systems and development practices.
- 2 years of experience in data science product delivery.
**Education**:
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
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