Job Description
Are you a Data Analyst passionate about transforming raw data into actionable business insights? Join our elite team in the heart of San Francisco and drive data-driven decision-making at a global scale.
We are looking for a highly analytical and detail-oriented professional to join our growing Analytics team. In this role, you will collaborate with cross-functional stakeholders to identify trends, visualize complex data sets, and build scalable models that optimize our business operations.
Why Join Us?
- Competitive compensation package.
- Hybrid work model in the SF Bay Area.
- Access to cutting-edge data infrastructure and tools.
- Opportunity for professional growth and leadership.
Responsibilities
- Data Exploration & Analysis: Collect, clean, and analyze large, complex datasets to identify trends, patterns, and actionable insights.
- Visualization: Create intuitive, interactive dashboards using Tableau or Power BI to track key performance indicators (KPIs) and present findings to leadership.
- Collaboration: Partner with product managers, engineers, and business units to define data requirements and solve complex business problems.
- Reporting: Develop automated reporting systems and SQL scripts to streamline business intelligence workflows.
- Quality Assurance: Ensure data integrity and accuracy across all reporting platforms and databases.
- Forecasting: Build predictive models to support strategic planning and revenue forecasting.
Qualifications
- Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
- Experience: Minimum of 3-5 years of professional experience as a Data Analyst or Business Intelligence Analyst.
- Technical Skills: Proficiency in SQL (Advanced), Python or R, and experience with data visualization tools (Tableau, Looker, or Power BI).
- Statistical Knowledge: Strong understanding of statistical analysis methods, A/B testing, and data modeling.
- Soft Skills: Exceptional communication skills with the ability to translate technical data into clear, non-technical business recommendations.
- Tools: Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.