Job Description
Join our dynamic data team as a Night Shift Data Analyst in Boston, MA with full remote flexibility. We're urgently seeking analytical talent to transform complex datasets into actionable business insights. This critical role supports our 24/7 operations, requiring availability during overnight hours (10 PM - 6 AM EST). Enjoy competitive compensation, comprehensive benefits, and the opportunity to impact strategic decisions at a rapidly growing tech firm.
What you'll love: Flexible remote work options, cutting-edge analytics tools, and a collaborative culture that values data-driven innovation. Perfect for night owls seeking career advancement without geographical constraints.
Responsibilities
- Perform complex data analysis using SQL, Python, and advanced Excel functions to identify trends and anomalies
- Develop automated reporting dashboards in Tableau/Power BI for real-time business intelligence
- Collaborate with cross-functional teams to translate data findings into actionable recommendations
- Monitor data quality pipelines and implement data governance best practices
- Create ad-hoc analyses to support urgent business initiatives during night shift hours
- Document analytical methodologies and maintain data dictionaries for team knowledge sharing
- Present findings to stakeholders through clear visualizations and concise executive summaries
Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, or related field
- 3+ years of professional data analysis experience with night shift or 24/7 environment exposure
- Expert proficiency in SQL, Python (Pandas, NumPy), and advanced Excel functions
- Strong experience with data visualization tools (Tableau, Power BI, or similar)
- Proven ability to work independently and deliver results during non-standard hours
- Excellent problem-solving skills with attention to detail and accuracy
- Strong written and verbal communication skills for remote stakeholder engagement
- Experience with cloud data platforms (AWS, Azure, or GCP) preferred