Central Analytics Lead - Growth - Marketing

Job Description

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.