Job Description
Join our dynamic data team as a Night Shift Data Analyst and revolutionize how businesses make decisions through data-driven insights. This fully remote position offers competitive compensation and the flexibility to work from anywhere in the United States while supporting our West Coast operations. You'll transform complex datasets into actionable strategies for clients across Las Vegas, NV, and California, working during evening hours to ensure seamless collaboration with global teams.
Why Nexus Analytics? We pride ourselves on fostering a culture of innovation and growth, with opportunities for professional development and a collaborative remote-first environment. Our analysts enjoy comprehensive benefits, including health insurance, 401k matching, and flexible scheduling to support work-life balance.
Responsibilities
- Analyze large datasets using SQL, Python, and BI tools 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 data quality and implement validation protocols to ensure accuracy
- Present findings to leadership through compelling visualizations and clear narratives
- Optimize data pipelines for efficiency and scalability across multiple time zones
- Support California-based clients during night shift hours (8 PM - 5 AM PT)
Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, or related field
- 3+ years of experience in data analysis or business intelligence roles
- Proficiency in SQL, Python (Pandas, NumPy), and data visualization tools
- Experience with ETL processes and cloud platforms (AWS/GCP/Azure)
- Strong problem-solving skills with attention to detail and accuracy
- Ability to work independently during night shift hours with minimal supervision
- Excellent communication skills for translating technical insights to non-technical audiences
- Portfolio demonstrating past data projects and visualizations