Data BI Analyst (Entry Level) - US/Canada

Data BI Analyst (Entry Level) - Remote Job, US/Canada, 1+ Year Experience About us: Patterned Learning is an AI-powered platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.

After applying for a position, please follow our page for further updates. Requirements Mandatory Skills Description: - Bachelor's Degree required with an emphasis in business, economics, math, engineering, or analytics preferred (or relevant work experience). Advanced degree or certification preferred. - 1+ years, with at least 1 year of analytic experience - Proficiency in interacting with various database and file storage systems (Examples: Oracle, Hadoop, NoSQL).

Understanding of join types. - Experience with data manipulation languages, such as SQL, required - Knowledge of statistical concepts and analytic techniques, including descriptive statistics, forecasting, economic modeling, exploratory analysis, and variance analysis required. - Ability to perform univariate analytic analytical techniques - Experience using Microsoft Excel, including the use of pivot tables, formulas, macros, VBA, charts/graphs - Experience with visualization tools such as Tableau, PowerBi, or QlikView.

- Strong analytical, critical, and systems thinking required. Nice-to-Have Skills: - Good understanding of Agile framework (SCRUM) - Familiarity with Salesforce is a plus. Why Patterned Learning AI? By leveraging AI, Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This AI-powered assistance can help reduce coding errors, improve productivity, and accelerate the development process.

The use of AI in pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.