Manager- Data Analytics

Job Description

Responsibilities: Develop and execute a data strategy to align with product development and business objectives. 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. ualifications: Education: Bachelors 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., SL, Python, R, Tableau, Power BI). Excellent leadership, communication, and presentation skills. Ability to translate data insights into actionable business recommendations. Knowledge of ML, data governance, data quality, and data protection practices.