Transform, and clean a large complex dataset using Python and SQL
Develop and implement advanced analytical models and algorithms to uncover trends, patterns, and opportunities in e-commerce data
Collaborate with cross-functional teams to understand client objectives, define analytical requirements, and deliver customized solutions
Communicate findings and recommendations effectively through clear visualizations, statistical results, and reports
Continuously enhance analytical methodologies and processes to improve efficiency and effectiveness
Stay updated with industry trends and best practices in data analysis and e-commerce

Exceptional analytical and problem-solving skills with a solid foundation in statistics and the ability to independently draw conclusions from complex datasets
Proficiency in Python, SQL, Google Sheets, and Excel is essential; experience with data visualization tools (e.g., Tableau, Power BI) is a plus
Proficiency in data warehouse platforms (e.g., Snowflake, Amazon Athena, Google BigQuery) for complex querying, analytics, and pipeline scheduling is essential
Proactive, curious, and highly tenacious, with a strong drive to grow and stay ahead of industry trends
Comfortable navigating a fast-paced, ambiguous environment with a high degree of independence
Passionate about e-commerce, with strong communication skills and the ability to convey technical concepts clearly to non-technical stakeholders; experience with client-facing communication is a plus
A Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, etc.) is preferred but not required.

Data Analyst, Mid-Level

Key skills