Senior Product Analyst
New
X
XsollaConsumer Technology
Based in United StatesFull-TimeSenior
Salary125,000 - 180,000 USD per year
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Job Details
- Experience
- At least 5 years
- Required Skills
- SQLTableauProduct AnalyticsData visualizationA/B testingLooker
Requirements
- Bachelor’s degree in Mathematics, Statistics, Economics, or a related quantitative discipline.
- At least 5 years of experience in quantitative or product analytics in gaming, advertising, or consumer technology.
- Advanced SQL skills for querying and interpreting complex, high-dimensional datasets.
- Strong statistical capabilities to select appropriate methodologies and translate results into business recommendations.
- Hands-on experience with Statsig or comparable A/B testing and experimentation platforms.
- Strong proficiency with BI and data visualization tools like Looker or Tableau.
- Experience with product analytics tools such as Mixpanel or Amplitude.
- Expertise in product funnels, cohort analysis, user behavior, KPIs, and growth analytics.
- Excellent communication and stakeholder-management skills for both technical and non-technical audiences.
- Ability to prioritize effectively and manage multiple initiatives in a fast-paced environment.
- Preferred: Experience with machine learning or predictive modeling in a product context.
- Preferred: Background in advertising, performance marketing, monetization analytics, or free-to-play gaming metrics.
Responsibilities
- Own product and data analysis for consumer-facing applications and websites to improve user engagement, rewards, retention, and performance.
- Conduct descriptive, diagnostic, and prescriptive analyses including product funnels, cohort analysis, and behavioral modeling.
- Define and monitor product KPIs and develop automated dashboards and analytical models for data-informed decision-making.
- Design, coordinate, execute, and analyze multivariate A/B experiments to evaluate new features and identify growth opportunities.
- Translate complex analytical findings into actionable recommendations for Product, Engineering, and Operations stakeholders.
- Apply advanced analytics and machine learning techniques to uncover insights, forecast trends, and inform monetization strategies.
- Partner with cross-functional teams to develop business cases and data-backed recommendations for new product initiatives.
- Contribute to the development of analytics infrastructure and experimentation frameworks for scalable decision-making.
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