- 경험
- 어느
- 샐러리
- —
- 채용 공고
- 1
- 게시됨
- 20시간 전
- 작업 모드
- 사무실에서
- 교육
- Bachelor's degree in Data Analytics or related field
- 재개하다
- 신청 시 필수 사항
당신이 일하게 될 곳
직무 설명
Role Overview
This position is designed for entry-level professionals who will gather, organize, analyze, and interpret data to aid business decision-making and operational enhancements. The role entails working with diverse datasets to recognize patterns, produce reports, and provide valuable insights to assist teams in informed decision-making.
Key Responsibilities
- Collect and clean data from various sources to maintain accuracy.
- Analyze datasets to uncover trends and insights relevant to business goals.
- Create detailed reports, dashboards, and visual representations of data.
- Track key performance indicators and essential business metrics.
- Ensure data quality through rigorous validation and maintenance standards.
- Support business reporting and contribute to analytical projects.
- Document analytical workflows and findings for future reference.
- Collaborate with business stakeholders and technical teams to facilitate decision-making.
- Identify process improvements to enhance reporting efficiency and data handling.
- Continuously learn and implement new analytical tools and methodologies.
Qualifications and Skills
- Fundamental understanding of data analysis principles and reporting methods.
- Proficiency in Microsoft Excel or equivalent spreadsheet applications.
- Basic knowledge of SQL is advantageous.
- Experience with data visualization platforms such as Power BI or Tableau is beneficial.
- Elementary familiarity with Python or R for data analysis is a plus but not mandatory.
- Strong analytical thinking and problem-solving capabilities.
- High attention to detail coupled with organizational skills.
- Effective communication and ability to work collaboratively within teams.
- Motivation to learn emerging analytical technologies and techniques.
- Preferred educational qualifications include degrees in Data Analytics, Business Analytics, Computer Science, Information Systems, Statistics, Mathematics, Economics, Finance, or closely related disciplines.