Product Analyst

Why Join Us?

• Proven Success: Work under investors who have spearheaded successful exits, including the sale of Looksery and AI Factory to Snap for $150M and $166M, respectively.
• Rapid Growth: Be part of a thriving company generating $3M ARR and serving 150,000 satisfied customers across the US and Europe.
• Innovative Projects: Contribute to cutting-edge AI-driven initiatives in a dynamic and fast-paced startup environment.
• Top Talent: Collaborate with experts from leading companies like Lensa, Picsart, Viber, AIRI, and Yandex.

About the Role

As a Product Analyst at Glam, you will play a pivotal role in driving data-informed decisions to optimize our AI-powered platform. By leveraging your expertise in data analysis, A/B testing, and performance tracking, you will identify growth opportunities, shape product strategies, and ensure seamless user experiences. If you’re passionate about turning data into actionable insights and thrive in a startup environment, we’d love to hear from you.

Key Responsibilities

• Analyze user behavior and product performance to identify trends and actionable insights.
• Develop and maintain dashboards to track key metrics, providing clear visibility into the product's health.
• Design and execute A/B tests to evaluate the effectiveness of new features and initiatives.
• Collaborate with Product, Engineering, and Marketing teams to guide product development with data-driven recommendations.
• Drive user segmentation analysis to improve targeting, retention, and user satisfaction.
• Communicate findings and recommendations clearly to stakeholders, both technical and non-technical.
   

Qualifications

1. Experience:
   • Proven track record of using data to influence product decisions and outcomes.
   • Hands-on experience with A/B testing frameworks and tools.
2. Technical Skills:
   • Expertise in product analytics tools such as Amplitude, Adapty, and Firebase for tracking and insights.
   • Advanced analytical and statistical skills
   • In-depth understanding of key app performance metrics like DAU, MAU, LTV, CAC, and churn
3. Additional Skills (Preferred):
   • Hands-on experience in Python or R for data analysis and modeling.
   • Experience with AI-driven platforms or consumer apps.
   • Familiarity with user funnel analysis and retention modeling.
   • Understanding of marketing analytics and campaign performance tracking.

Application Process

1. Resume Screening
2. Initial Phone Screen (~15 minutes)
3. Technical Assessment/Interview (~1.5 hours)
4. Final Interview → Offer and Onboarding (~15 minutes)

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