Senior Manager - Data Analytics

Key Responsibilities

• Develop and execute a data strategy to align with product development and business objectives.
• Lead and mentor the team of data analysts and BI professionals.
• Foster data-driven decision-making throughout the product lifecycle, from development to marketing.
• Oversee data collection, analysis, and interpretation to provide actionable insights for product improvement.
• Ensure timely delivery of accurate reports, dashboards, and visualizations to support product decisions.
• Integrate new data sources and technologies to innovate and optimize product analytics.
• Define and track product-specific KPIs and metrics to measure performance and inform strategy.
• Provide insights and recommendations to support strategic product initiatives and enhancements.
• Assess the impact of data-driven projects on product success and user experience.
• Advocate for the value of data analytics in driving product innovation and growth.
• Communicate complex data concepts to non-technical stakeholders to inform product strategy.
• Collaborate with cross-functional teams to understand and address product data needs effectively.
• Share success stories and case studies to illustrate the impact of data-driven product improvements.
• Stay updated on industry trends and advancements in product analytics and technology.
• Foster innovation in analytical techniques and methodologies to stay ahead in the competitive landscape.
• Encourage continuous learning and development within the data team to maintain a high standard of expertise in product analytics.
  

Qualifications

Education:

• Bachelor’s degree in Computer Science, Statistics, Data Science, or a related field. Advanced degree preferred.
  

Experience

• Extensive experience in data analytics or business intelligence, with a proven track record of leadership.
  

Skills

• Successful implementation of data strategies and fostering data-driven cultures.
• Strong expertise in statistical analysis, data modeling, and data visualization.
• Proficiency with analytics tools (e.g., SQL, Python, R, Tableau, Power BI).
• Excellent leadership, communication, and presentation skills.
• Ability to translate data insights into actionable business recommendations.
• Knowledge of data governance, data quality, and data protection practices.