
Data Analyst
3 days ago
Key Accomplishments and Skills
- Data Management & Reporting: Own and maintain core datasets, ensuring
accuracy, completeness, and consistency for business reporting. - Automation & Dashboards: Build and maintain automated reports and dashboard
to support both business and investor needs. - Insight & Strategy: Identify key trends, patterns, and insights to inform business strategy and operational improvements.
- Cross-Functional Collaboration: Partner with teams such as Finance, Product,
Marketing, and Operations to understand data requirements and deliver actionable insights. - Data Quality & Integrity: Monitor and resolve inconsistencies in data quality across various systems to ensure reliable reporting.
- Performance Analysis: Provide timely analysis on business performance, user behavior, revenue trends, and other key metrics.
- Process Improvement: Develop and document data processes, definitions, and reporting standards to enhance efficiency and consistency.
- Stakeholder Communication: Present complex findings in a clear and compelling manner to stakeholders at all levels, supporting ad-hoc data investigations and reporting requests.
Key Qualifications & Requirements
- Education: Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering.
- Experience: 1-2 years of professional experience in a data analyst or data engineering role. We also welcome applications from career switchers with a demonstrated aptitude for data analysis.
Technical Skills:
- Proficiency in Python and SQL.
- Experience with at least one data visualization tool (e.g., Power BI, Tableau, Looker).
- Strong knowledge of Excel or Google Sheets.
Core Competencies:
- Exceptional problem-solving skills and meticulous attention to detail, with a strong commitment to data accuracy and reliability.
- Proven ability to work independently, manage multiple priorities, and thrive in a fast-paced environment.
- Excellent communication skills, with the ability to clearly and effectively present complex data findings to both technical and non-technical audiences.
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