Business Data Analyst (World Wine List (Wwl) Platform)

As a Business Data Analyst at World Wine List (WWL) platform, your primary responsibility will be to gather, analyze, and interpret data to provide actionable insights that will drive business decisions and enhance the overall performance of the platform. You will work closely with cross-functional teams, including product managers, marketing, and engineering, to identify key performance indicators (KPIs) and develop data-driven solutions to improve the platform's user experience and business operations.

Responsibilities:

1. Data Collection and Analysis: Gather data from various sources, including databases, APIs, and third-party tools. Conduct thorough data analysis to identify trends, patterns, and opportunities for improvement.
2. Reporting and Visualization: Create clear and concise reports, dashboards, and data visualizations to communicate insights to stakeholders and management. Translate complex data into actionable recommendations.
3. Performance Metrics: Define and track key performance metrics (KPIs) to measure the success of the platform and identify areas for optimization.
4. Business Insights: Analyze user behavior, engagement, and retention to understand user preferences and recommend strategies for enhancing the user experience.
5. A/B Testing: Collaborate with product managers to design and implement A/B tests to evaluate the impact of new features and improvements.
6. Data Integrity and Validation: Ensure data accuracy, completeness, and consistency across different data sources.
7. Business Strategy: Assist in the development of business strategies based on data-driven insights and industry trends.
8. Stakeholder Collaboration: Work closely with cross-functional teams to understand their data needs and provide analytical support to address business challenges.
9. Data Governance: Implement data governance policies and best practices to maintain data security and compliance.

Requirements:

1. Education: Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a related field. A master's degree is a plus.
2. Analytical Skills: Strong analytical and problem-solving abilities with the capability to interpret complex data sets.
3. Technical Proficiency: Proficiency in data querying languages (SQL) and data visualization tools (Tableau, Power BI, etc.).
4. Data Tools: Experience with data manipulation and analysis using tools like Python, R, or Excel.
5. Business Acumen: Understanding of business operations, market dynamics, and industry trends.
6. Communication: Excellent verbal and written communication skills to convey complex data findings to non-technical stakeholders effectively.
7. Team Player: Ability to collaborate effectively with cross-functional teams and contribute to a positive team environment.
8. Attention to Detail: Strong attention to detail to ensure data accuracy and validity.
9. Adaptability: Willingness to learn and adapt to new technologies and methodologies in data analysis.