This role requires a strong analytical mindset, exceptional attention to detail, and the ability to recognize trends and opportunities in complex datasets. While this is not a heavily customer-facing role, effective communication skills are essential for presenting insights clearly and effectively to internal teams and clients.

Key Responsibilities:

• Data Analysis and Pattern Recognition:  Analyze customer performance data to identify trends, anomalies, and actionable insights for improving pricing strategies and performance optimization.
• Strategic Recommendations:  Provide clear, data-backed recommendations for changes to pricing settings or shifts between profit and revenue optimization based on performance metrics.
• Results Interpretation:  Collaborate with the Customer Success and Data Science teams to translate analytical findings into practical business strategies.
• Performance Monitoring:  Regularly review and report on customer performance, highlighting successes and areas for improvement.
• Data Communication:  Effectively communicate complex findings and insights in a clear and concise manner to both technical and non-technical audiences.
• Attention to Detail:  Ensure the accuracy and consistency of data insights, maintaining high standards of quality in all deliverables.
• Process Improvement:  Identify opportunities to refine data analysis processes and develop playbooks for streamlined workflows.
• Collaboration:  Work closely with cross-functional teams, including Data Science, Technology, and Customer Success, to ensure seamless delivery of insights and solutions.
• Attention to detail: To confirm your attention to detail, include your favorite 90s band in your application.

Qualifications:

You:

• Have a strong academic background in Mathematics, Statistics, Engineering, Data Science, or a related field.
• Demonstrate exceptional analytical skills, with a proven ability to identify patterns and insights in data.
• Possess excellent attention to detail and accuracy in data handling and reporting.
• Are proficient in tools such as Excel, PowerPoint, and data visualization platforms.
• Have strong written and verbal communication skills to articulate findings and recommendations effectively.
• Are comfortable collaborating with cross-functional teams to ensure data-driven decisions are actionable and impactful.

Bonus if you:

• Have experience with programming languages (e.g., Python, R) for data analysis. Understand P&L statements and financial modeling. Are familiar with eCommerce platforms or SaaS business models.
• Have experience using tools like PipeDrive or other CRM systems.