Data Analyst (AI Infrastructure)

Job Description

Responsibilities:

• AI Data Pipeline Management: Assist in building, maintaining, and optimizing data pipelines that feed AI and machine learning models with clean, structured, and accurate data.
• Data Quality Assurance: Monitor, validate, and preprocess large datasets to ensure data integrity and reliability for AI training and inference.
• Infrastructure Collaboration: Work closely with data engineers and AI teams to translate computational needs into scalable infrastructure solutions, leveraging cloud platforms (AWS, Azure, Google Cloud) and automation tools.
• Data Transformation & Integration: Support the development and maintenance of data warehouses, data lakes, and integration frameworks to streamline data flow for analytics and AI workloads.
• Performance Monitoring: Track and report on the performance of data infrastructure, identifying bottlenecks and opportunities for optimization.
• Process Improvement: Document workflows, automate repetitive tasks, and implement best practices for data governance and observability.

Learning Outcomes:

• Hands-on experience with AI/ML data workflows, cloud infrastructure, and big data tools.
• Exposure to automated data validation, ETL processes, and data observability platforms.
• Mentorship from experts in AI infrastructure, data engineering, and blockchain analytics.

Qualifications

Core Requirements:

• Technical Proficiency: Strong foundation in Python, SQL, and data manipulation libraries (Pandas, NumPy).
• Data Management Skills: Experience with data cleaning, preprocessing, and quality assurance for AI/ML applications.
• Cloud & Automation: Familiarity with cloud platforms (AWS, Azure, Google Cloud) and automation tools (Terraform, Ansible, Docker, Kubernetes) is a plus.
• Analytical Mindset: Ability to troubleshoot data anomalies, optimize data flows, and collaborate with cross-functional teams.
• Remote Work Ethic: Self-motivated with strong time management and communication skills for remote collaboration.
• Academic Background: Pursuing or holding a degree in Data Science, Computer Science, Engineering, or a related field.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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