Senior Client Analyst
Harnham, Austin, TX, United States
Job Title: Senior Client Analyst
Location: Austin, TX (Hybrid, 2-3 days in office)
Salary: $115,000 - $140,000 base + benefits
Are you an experienced analyst passionate about making a tangible difference in education? Join a pioneering EdTech company on a mission to increase graduation rates across the U.S. using cutting-edge, tech-enabled services.
Why You’ll Love This Role:
- Innovative Culture: Work in a fast-paced, creative environment with a small, highly collaborative team.
- Impactful Work: Directly contribute to improving student outcomes and educational success.
- Career Growth: Thrive in an expanding company with ample room for professional development.
Role Overview:
As a Senior Client Analyst, you’ll empower the Partner Success team by turning complex datasets into actionable insights. You’ll support account managers, optimizing how data is presented to clients and developing strategic recommendations. Key aspects of the role include A/B testing, performance analysis, and cross-functional collaboration.
Key Responsibilities:
- Interpret and manage large, multi-level datasets for valuable insights.
- Apply advanced statistical methods to analyze client data and address complex challenges.
- Develop, run, and evaluate A/B tests to drive improvements in student outcomes.
- Build and present data-driven reports and dynamic dashboards to support decision-making.
- Independently create reports that provide performance analysis, insights, and actionable recommendations for clients.
- Consistently deliver high-quality data insights and strategic advice with minimal supervision.
Your Skills & Experience:
- Degree in Mathematics, Statistics, Economics, Business, or related field.
- 4+ years of experience in analytics
- Expert level SQL skills
- Proficiency in data visualization tools (e.g., Tableau).
- Solid grasp of statistical analysis (e.g., correlation, regression).
- Ability to communicate data-driven insights and lead discussions across teams.
- Experience with machine learning or predictive modeling is a plus.