Shiprocket - Lead - Central Analytics

Central Analytics Lead

About the Role:

- We are seeking a highly analytical and data-driven individual to join our team as a Central Analytics Lead. In this role, you will play a critical role in driving data-driven decision-making across the organization. You will be responsible for building and scaling our central analytics function, identifying key business opportunities, and enabling data-informed strategies across all departments.

Key Responsibilities:

- Develop and implement robust data analysis frameworks and methodologies.

- Build and maintain data dashboards and reports to track key business metrics and monitor performance.

- Conduct in-depth data analysis to identify trends, uncover insights, and inform strategic decisions.

- Develop and present data-driven presentations to stakeholders across the organization.

- Collaborate closely with cross-functional teams (product, marketing, sales, operations) to understand their data needs and provide actionable insights.

- Build and mentor a high-performing team of analysts (future expectation).

- Identify opportunities for data-driven innovation and process improvement.

- Ensure data quality and integrity across all systems.

- Stay abreast of the latest advancements in data analytics and visualization.

Qualifications:

- 4+ years of experience in an analytics role, preferably in a high-growth startup environment.

- Exceptional SQL skills and experience with data warehousing and ETL processes.

- Strong experience with data visualization tools (e.g., Tableau, Power BI, Looker).

- Excellent communication, presentation, and storytelling skills.

- Ability to translate complex data into actionable insights and recommendations.

- Strong analytical and problem-solving skills with the ability to think critically and independently.

- Growth mindset with a strong desire to learn and adapt to new challenges.

- Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or a related field.

Bonus Points:

- Experience building and scaling data infrastructure and systems.

- Experience with machine learning and predictive modeling techniques.