Product Data Analyst

As a Product Data Analyst in the AI Team at 365Scores, you will play a crucial role in transforming complex data into actionable insights that drive our AI-driven product features. You will collaborate with cross-functional teams to analyze user behavior, develop key performance metrics, and support the continuous improvement of our AI applications. Your work will directly influence product strategies and enhance user experiences for millions of sports fans globally.

Requirements:

Proven experience (3+ years) as a Data Analyst, preferably within a product or technology-focused company.
Proficiency in SQL, Python, R, and data visualization tools such as Tableau or Power BI. Experience with machine learning frameworks is a plus.
Strong analytical and problem-solving skills with a data-driven approach to decision-making.
Excellent verbal and written communication skills, with the ability to translate complex data insights into actionable recommendations for non-technical stakeholders.
High level of accuracy and attention to detail in data analysis and reporting.
Ability to work collaboratively in a cross-functional team environment.
Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.
Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related field.

Responsibilities:

Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that support product decisions and strategies.
Develop, track, and maintain key performance indicators (KPIs) to evaluate the effectiveness of AI features and overall user engagement.
Design, implement, and analyze A/B tests to assess the impact of new features and optimizations.
Create and maintain detailed reports and interactive dashboards to communicate findings and monitor product performance.
Work closely with product managers, data scientists, engineers, and other stakeholders to integrate data-driven insights into product development processes.
Conduct user research and usability studies to gather qualitative data, complementing quantitative analysis.
Ensure the accuracy and consistency of data collected from various sources and support data cleaning and preprocessing activities.
Utilize machine learning models and statistical techniques to predict user behavior and identify opportunities for product enhancements.
Maintain clear and comprehensive documentation of methodologies, analyses, and processes to ensure reproducibility and knowledge sharing.