Responsibilities:
• Lead and manage data analysis projects from conception through execution, ensuring timely and successful delivery.
• Define project scope, objectives, and deliverables in collaboration with stakeholders.
• Develop detailed project plans, including timelines, resource allocation, and risk management strategies.
• Oversee the collection, analysis, and interpretation of investment-related data to generate actionable insights.
• Utilize statistical tools and data analysis software to assess investment opportunities, performance, and risks.
• Ensure data accuracy and integrity in all analyses and reports.
• Prepare and present comprehensive reports and visualizations to senior management and other stakeholders.
• Translate complex data findings into clear, actionable recommendations and strategic insights.
• Develop dashboards and reporting tools to track key investment metrics and performance indicators.
• Work closely with investment analysts, finance teams, and other departments to understand their data needs and provide support.
• Facilitate communication between project teams and stakeholders to ensure alignment and address any issues or changes.
• Identify opportunities for improving data collection, analysis processes, and reporting methods.
• Implement best practices and new technologies to enhance project efficiency and data accuracy.
Qualifications:
• Bachelor’s degree in Data Science, Statistics, Business Administration, or a related field.
• A Master’s degree or relevant certification (e.g., PMP, Six Sigma) is a plus.
• Minimum of 5 years of experience in project management with a focus on data analysis.
• Experience in the sports or golf industry is highly desirable.
Skills and Competencies:
• Proficiency in data analysis tools (e.g., SQL, Python, R) and data visualization software (e.g., Tableau, Power BI).
• Strong project management skills with experience in leading cross-functional teams and managing complex projects.
• Excellent analytical and problem-solving skills with the ability to interpret complex data and present findings clearly.
• Strong written and verbal communication skills, with the ability to convey technical information to non-technical stakeholders.
• Proven leadership abilities with experience in managing and mentoring team members.