Overview
On Site
Depends on Experience
Full Time
Skills
Computer Vision
Artificial Intelligence
Data Analysis
Machine Learning (ML)
Analytics
Data Processing
NumPy
Pandas
Python
scikit-learn
Reliability Engineering
Continuous Improvement
Job Details
Strong Hands-on Python Programming, Python Libraries (Numpy, Pandas, Scikit -Learn) for Data Analytics, Computer Vision, AI & Machine Learning, SRE Principle, Tenser flow & Pytorch
Responsibilities:
- Implement data analytics techniques using Python, employing libraries such as pandas, NumPy, and scikit-learn to enable efficient and scalable data processing workflows.
- Create and interpret visually compelling graphs and visual data representations to effectively communicate analytical findings to both technical and non-technical stakeholders.
- Apply Site Reliability Engineering (SRE) principles to ensure the scalability, reliability, and performance of AI/ML infrastructure supporting computer vision models.
- Participate in troubleshooting and resolving high-priority critical issues in analytics environments, such as those encountered in CrowdPulse analytics, ensuring data accuracy and system stability.
- Lead biweekly review meetings for analytics projects, generating clear documentation, sharing progress updates, and fostering continuous improvement through collaborative feedback.
- Identify and respond promptly to analytical anomalies, providing innovative solutions and recommendations to enhance model and system performance.
- Earn recognition for high performance and dedication, as exemplified by awards such as inclusion on the 'Wall of Fame' for outstanding contributions.
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