Data Analyst (Remote, Graveyard)

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Requirements:

• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field
• 3 years of experience in data analysis, preferably within a SaaS or subscription-based business environment.
• Strong understanding of subscription churn metrics, customer segmentation, and cohort analysis.
• Experience with data visualization tools such as Tableau, Looker, or Power BI preferred
• Familiarity with machine learning techniques for predictive modeling and customer behavior analysis is preferred
• Excellent communication skills with the ability to translate complex data findings into actionable insights for non-technical stakeholders.
• Proven track record of driving business impact through data-driven decision-making.
• Experience working with subscription management platforms (e.g., Zuora, Chargebee, Stripe) preferred
• Strong proficiency in Excel and Google Sheets, with a focus on utilizing formulas and effectively organizing and structuring data
• Attention to detail and a commitment to data accuracy and integrity.
• Previous exposure to customer success or retention-focused roles preferred

Responsibilities:

• Analyze subscription churn patterns and develop predictive models to forecast customer attrition rates.
• Identify key factors influencing customer retention and engagement through comprehensive data analysis.
• Collaborate with product and marketing teams to implement targeted retention campaigns based on data insights.
• Monitor subscription KPIs such as MRR (Monthly Recurring Revenue), customer lifetime value (CLV), and churn rate.
• Conduct A/B testing and experimentation to optimize onboarding processes and reduce churn.
• Utilize data visualization tools to create actionable dashboards and reports for stakeholders.
• Partner with customer success teams to implement proactive measures for customer satisfaction and loyalty.
• Partner with sales teams to analyze sales processes and identify areas for optimization and efficiency improvements.
• Analyze internal application workflows (e.g., customer support, billing) to streamline operations and enhance user experience.
• Continuously assess data quality and integrity to ensure accuracy and reliability of analytics outputs.