Job Description
Join DataInsights Global as a Part-Time Data Analyst and unlock exciting career opportunities in Phoenix's thriving tech hub! We're offering generous relocation assistance for qualified candidates seeking to relocate to Arizona. This flexible role combines analytical rigor with strategic impact, allowing you to transform raw data into actionable business insights while enjoying work-life balance. Our Phoenix-based team collaborates on cutting-edge projects for Fortune 500 clients, offering mentorship from industry veterans and exposure to advanced analytics tools. Relocation package includes moving stipend, temporary housing assistance, and onboarding support to ensure a smooth transition to the Valley of the Sun.
Responsibilities
- Analyze complex datasets using SQL, Python, and statistical modeling to identify trends and business opportunities
- Create interactive dashboards and reports using Tableau/Power BI for executive stakeholders
- Collaborate with cross-functional teams to define data requirements and deliver actionable insights
- Monitor KPIs and performance metrics, providing regular updates to leadership
- Develop automated data pipelines to improve reporting efficiency and accuracy
- Present findings to non-technical audiences through clear visualizations and narratives
- Maintain data integrity through rigorous validation and quality control processes
Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, or related field
- 2+ years of experience in data analysis or business intelligence roles
- Proficiency in SQL, Python (Pandas, NumPy), and visualization tools (Tableau/Power BI)
- Strong statistical knowledge and experience with A/B testing methodologies
- Excellent communication skills with ability to translate technical concepts to business stakeholders
- Proven track record of delivering data-driven solutions in a collaborative environment
- Experience working with large datasets and cloud platforms (AWS/GCP/Azure)
- Ability to work independently with minimal supervision in a flexible schedule