About us:
At Cognira, we strongly believe that people are the biggest asset of our company. Our hand-picked team consists of passionate, collaborative, and forward-thinking individuals from all over the globe. We are passionate about making science easy and accessible to retailers, helping them get more value from people, data, and systems. We bring together expertise in retail, science, and scalable technologies to automate and enhance the quality of decision-making through software and consulting services.For the last three years in a row, Cognira has been recognized as one of the fastest-growing companies in North America.
We are proud to have a growing team of domain experts and data scientists, as well as a culture that fosters strong and long-lasting relationships with our clients. Our values:
- Stand up for what’s right
- Customers are always first
- Think like an Entrepreneur. Act like a CEO.
- Learn, Unlearn, Relearn
- No brilliant jerks allowed
- All work and no play is no fun at all
Important: Please submit your resume in English only.About the Project :Project Name: "Defect Trend Analysis for Quality Assurance Process Optimization"Project Description: The goal is to analyze defect data from Quality Assurance cycles to uncover patterns, identify root causes to enhance the efficiency and accuracy of defect management within the software development lifecycle (SDLC) by implementing an AI-driven classification system for Jira bug tickets. This will be achieved by analyzing text-based inputs (e.g., ticket descriptions, comments) and additional features (e.g., issue type, testing phase, occurrence frequency) to automatically classify tickets by priority, component, defect type, and team assignment.The project will involve training machine learning models, such as NLP-based or deep learning models, to identify patterns and categorize tickets based on historical data.
This classification will improve prioritization, streamline workflows, and enable better resource allocation, reducing manual effort and minimizing errors.Skills and Techniques:
- Tools:
- Defect tracking: JIRA
- Data analysis: Python (pandas)
- Visualization: Tableau, Power BI, or matplotlib/seaborn (if using Python)
- Techniques:
- Statistical analysis (e.g., Pareto Principle for defect prioritization)
- Root Cause Analysis (RCA) techniques (e.g, 5 Whys, Fishbone Diagrams)
- Defect clustering by modules/features
- Machine Learning
- Natural Language Processing (NLP)
[ Important: Please send us your resume in English only ]What you'll enjoy here:It's not just an internship; we've got some great added value for you too. Here's what you'll enjoy:
- Great company culture.
- "Learn and Share" sessions.
- You'll get support from your mentors.
- Social events and after-work.
- A flexible and fun work environment.
- Casual dress code.
- You'll work with a cool team! We respect your ideas, and we're all about trying new things.
- Work/life balance
[ Important: Please send us your resume in English only ]
