We are looking for a smart, research-driven, and highly analytical Product Analyst to help shape the future of our AI Interviewer feature — a cutting-edge tool designed to help job seekers land roles in top-tier tech companies like Amazon, Google, Meta, and other FAANG firms. As a Product Analyst, you will play a critical role in evaluating the effectiveness of the mock interview experience, understanding how real interviews are structured in the U.S. (especially at FAANG), and providing continuous, structured feedback to enhance the product.

Job Responsibilities

• Research and understand interview processes for various roles (e.g., Data Engineer, AI Product Manager) at major U.S. tech companies.
• Break down interview stages (screening, technical rounds, system design, behavioral, etc.) to ensure our AI Interviewer reflects real-world structures.
• Evaluate current AI Interviewer functionality by taking mock interviews, reviewing session recordings, and simulating end-to-end user journeys.
• Collect and analyze user feedback (qualitative and quantitative) to identify pain points and areas for improvement.
• Translate research findings into clear product recommendations and present them to the technical and product teams.
• Assist in designing new mock interview scenarios, question sets, and evaluation criteria aligned with industry best practices.
• Monitor feature performance over time and support A/B testing and optimization efforts.

Skills Required

• Strong understanding of U.S. tech hiring practices, particularly at companies like Amazon, Google, Meta, Netflix, and Apple (FAANG).
• Interest in HR tech, career coaching platforms, and ed-tech products.
• Excellent analytical and research skills — ability to break down complex processes and translate them into actionable insights.
• Strong written communication skills — capable of drafting structured reports and clear product documentation.
• Familiarity with mock interview platforms, career preparation tools, or applicant tracking systems (ATS).

Required Qualifications

• Bachelor’s degree (or currently pursuing) in Business, Computer Science, Data Science, Psychology, or a related field.

Job Experience

• Proven experience in product analysis, UX research, or a related field, with a focus on understanding and improving user experiences.
• Hands-on experience researching and analyzing tech hiring processes, particularly for roles within top-tier companies such as Amazon, Google, Meta, Netflix, and Apple (FAANG).
• Demonstrated ability to evaluate product functionality, including conducting mock interviews, reviewing session recordings, and simulating user journeys.
• Experience gathering and analyzing both qualitative and quantitative user feedback, identifying pain points, and suggesting actionable improvements.
• Familiarity with designing and developing product recommendations and communicating them effectively to cross-functional teams (e.g., engineering, product, and design teams).
• Involvement in creating new product scenarios, interview question sets, and evaluation criteria based on industry standards.
• Experience with A/B testing and performance tracking to measure and optimize product features.
• Familiarity with mock interview platforms, applicant tracking systems (ATS), or career preparation tools.

Other Benefits

• Work on a real-world AI-powered product that directly helps job seekers land top-tier tech roles.
• Gain hands-on experience in product research, UX analysis, and feature development.
• Collaborate with a dynamic, cross-functional team of engineers, designers, and career experts.
• A great stepping stone for a future career in product management, business analysis, or tech recruiting.

Job Working Hours

20 Per week

Equal Employment Opportunities

We provide Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, national origin, age, disability or genetics. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, compensation, and training.