Manager- Data Analytics

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.

Ǫualifications:

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., SǪL, 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.