Data Analyst for CloudKitchens

3 days ago


Los Angeles, California, United States CloudKitchens Full time
Unlock Career Growth as a Data Analyst

Are you passionate about data analysis and driving business decisions? We're seeking an exceptional Data Analyst to join our team at CloudKitchens As a key member of our People Analytics team, you'll play a vital role in unlocking insights that drive actionable clarity towards enabling a Just Workplace. With a focus on delivering information at scale, you'll collaborate across the broader People team and business leaders to support strategic decisions that attract, develop, and retain talent.

About the Role:
As a Data Analyst, you'll use information design and data science techniques to explore workforce dynamics, working closely with cross-functional teams to provide data-driven insights. You'll be responsible for delivering high-quality analytics projects, creating sophisticated visualizations, and developing advanced statistical models to predict and analyze workforce trends. Your work will help create a workplace where employees thrive, and your contributions will make a tangible impact on our organization's success.

What We Offer:
A competitive salary of $90,000 - $110,000 per year, based on location and experience. A collaborative environment where your ideas are valued and your contributions make a difference. Access to development resources to advance your skills and career. An inclusive culture where diversity is celebrated, and everyone feels empowered to grow. We're committed to creating a workplace where employees can thrive, and we're excited to welcome talented individuals like you to our team

Requirements:
Bachelor's degree in Data Science, Statistics, Computer Science, or a quantitatively-based social science field. 1-3 years of relevant work experience in data analysis, business intelligence, or related fields. Proficiency in statistical coding languages and tools (e.g., SQL, R, Python) and data visualization platforms (e.g., Tableau, Looker). Strong understanding of ETL processes, data pipeline development, and data integrity practices.

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