Job Description
Are you a data-driven professional looking to make an impact on the weekend? Apex Data Systems, a premier provider of top-tier technology solutions, is seeking a highly skilled Data Analyst to join our elite analytics team in Baltimore, MD. In this pivotal role, you will bridge the gap between complex datasets and actionable business strategies, working with top-tier stakeholders to optimize performance and drive growth.
We are looking for a self-motivated individual who thrives in a high-performance environment and possesses a keen eye for detail. As part of our weekend shift team, you will be responsible for ensuring our data infrastructure remains robust and our insights are delivered with precision.
What You Will Do:
• Extract, clean, and transform large datasets using advanced SQL and Python.
• Develop compelling visualizations in Tableau and Power BI to tell the story behind the numbers.
• Conduct in-depth A/B testing and statistical analysis to support product and marketing initiatives.
Responsibilities
- Perform complex data analysis and modeling to support business decision-making on weekends.
- Collaborate with cross-functional teams to define data requirements and generate actionable insights.
- Create and maintain interactive dashboards using Tableau and Power BI.
- Identify trends, patterns, and anomalies in large datasets to optimize operational efficiency.
- Ensure data quality and integrity through rigorous cleaning and validation processes.
- Document data pipelines and analytical methodologies for team knowledge transfer.
Qualifications
- Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field.
- 3+ years of experience in data analysis, preferably within the tech or financial sector.
- Proficiency in SQL (MySQL, PostgreSQL) and Python (Pandas, NumPy).
- Strong experience with data visualization tools such as Tableau or Power BI.
- Excellent communication skills to translate complex data into clear, concise reports.
- Ability to work independently and collaboratively during weekend shifts.