Product Analyst, AI & UX Optimization

📍 Job Overview

Job Title: Product Analyst, AI & UX Optimization

Company: Afficiency

Location: New York, New York, United States

Job Type: Full-time

Category: Product Operations / Revenue Operations (with a strong UX focus)

Date Posted: August 13, 2026

Experience Level: 2-5 Years

Remote Status: Hybrid

🚀 Role Summary

• Analyze product and UX/UI journeys to identify friction, confusion, and drop-off points, leveraging data from session recordings, support tickets, and conversion funnels.

• Utilize AI tools (e.g., Claude) to prototype and implement direct fixes for identified user experience issues, including copy changes, flow adjustments, and small tooling.

• Drive the end-to-end ownership of product improvements, from initial identification and scoping to implementation and success measurement.

• Collaborate closely with Product, Engineering, and Underwriting teams to scope and ship changes, ensuring seamless integration and escalation for complex technical work.

• Apply strong business judgment and common sense to prioritize issues and ensure solutions are practical, customer-centric, and aligned with business impact.

📝 Enhancement Note: While the title is "Product Analyst," the description strongly emphasizes hands-on execution, AI tool utilization for prototyping and implementation, and direct ownership of shipped improvements. This aligns closely with a Product Operations or even a Revenue Operations role focused on optimizing user journeys and conversion funnels, especially within a regulated industry like Insurtech. The "AI & UX Optimization" aspect highlights a forward-thinking approach to operational efficiency and customer experience enhancement.

📈 Primary Responsibilities

• Conduct in-depth analysis of user journeys across Afficiency's product suite, including application flows, agent tools, and consumer-facing experiences, to pinpoint areas of user confusion, friction, and abandonment.

• Dive deep into quantitative and qualitative data sources such as session replay recordings, customer support tickets, underwriting outcomes, and conversion funnels to diagnose root causes of user experience issues.

• Translate raw findings into actionable, prioritized recommendations that are directly linked to measurable business impact, focusing on tangible improvements rather than theoretical suggestions.

• Leverage AI tools (e.g., Claude) to rapidly prototype, build, and directly implement solutions, such as refining UI copy, adjusting user flows, developing minor tooling, or creating automation scripts, thereby reducing reliance on engineering for every fix.

• Partner effectively with cross-functional stakeholders including Product Managers, Engineers, and Underwriting teams to collaboratively scope, define, and execute product changes, ensuring clear communication and timely escalation for complex technical challenges.

• Establish and maintain a rigorous process for measuring the actual effectiveness of implemented changes, employing data-driven iteration to continuously refine and optimize user experiences based on performance metrics.

• Apply sound business acumen and critical thinking to evaluate the practicality and strategic value of proposed solutions, ensuring that efforts are focused on the most impactful and efficient improvements for customers and the business.

📝 Enhancement Note: The responsibilities detail a blend of analytical investigation and hands-on execution. The emphasis on using AI for prototyping and direct implementation, alongside measuring results, points towards a role that bridges the gap between analysis and operational delivery, common in advanced Product Operations or GTM Operations roles focused on customer journey optimization.

🎓 Skills & Qualifications

Education: Bachelor's degree in a related field is often preferred, but not explicitly required. The emphasis is on analytical ability and practical experience over formal education.

Experience: Approximately 2+ years of experience in business analysis, operations, product-adjacent roles, or similar analytical functions. A non-technical background is acceptable.

Required Skills:

• Proven analytical capabilities with a strong aptitude for identifying discrepancies and thoroughly investigating root causes.

• Excellent common sense and business judgment, with a keen eye for intuitive product design and process flow.

• Demonstrated self-starter mentality, capable of proactively identifying tasks and driving projects forward without constant direction.

• Strong ownership instinct; a proactive approach to problem-solving and a drive to personally implement solutions.

• Comfort and curiosity in learning and applying AI tools (such as Claude) as a practical means to accelerate analysis and execution, without requiring prior coding expertise.

• Clear and concise written and verbal communication skills, effective in articulating complex issues and their implications to both technical and non-technical audiences.

• Located within the NY tri-state area, with candidates outside this region not being considered. Preferred Skills:

• Prior experience within the insurance, fintech, or other regulated industries, providing context for complex product environments.

• Familiarity with product analytics tools, such as session replay software (e.g., FullStory, Hotjar), funnel analysis tools, or behavioral analytics platforms.

• Exposure to or basic understanding of SQL for data querying and analysis.

• Demonstrable hands-on experience using AI tools to build tangible outputs like workflows, automations, or prototypes, even in an informal capacity.

📝 Enhancement Note: The explicit requirement for candidates to be in the NY tri-state area is critical for a hybrid role. The emphasis on "ownership instinct" and using AI for "prototyping and shipping fixes" suggests a desire for a proactive, execution-oriented individual who can operate semi-autonomously, a valuable trait in operations roles that often require bridging gaps between departments.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies on UX/Flow Optimization: Showcase instances where you identified user friction points in a product or process and implemented solutions that demonstrably improved user experience, conversion rates, or efficiency. Quantify the impact where possible.

• Demonstration of AI Tool Application: Provide examples of how you've used AI tools (e.g., for content generation, workflow automation, prototyping, or data analysis) to achieve specific outcomes. Highlight the problem, your approach, and the results.

• Data Analysis & Insight Generation: Include examples of how you've analyzed user data (e.g., from session recordings, funnels, or support tickets) to derive actionable insights that led to product or process improvements.

• Process Improvement Documentation: Present documentation of a process you analyzed, optimized, or automated. This could include flowcharts, before-and-after comparisons, or detailed explanations of implemented changes and their impact.

Process Documentation:

• Evidence of analyzing complex user journeys and identifying key bottlenecks or areas for improvement.

• Examples of designing or refining workflows to enhance user experience, reduce drop-off rates, or increase task completion success.

• Documentation demonstrating how you measured the impact of changes, including the metrics used and the outcomes achieved.

📝 Enhancement Note: Given the role's focus on hands-on improvement and AI tool utilization, a portfolio should emphasize tangible outputs and measurable results. Case studies detailing the problem, the AI-assisted solution, and the impact are crucial. This is a key differentiator for operations roles that require demonstrating practical problem-solving skills beyond theoretical recommendations.

💵 Compensation & Benefits

Salary Range: $70,000 – $105,000 USD annually, commensurate with experience and qualifications.

Benefits:

• Robust health, dental, and vision insurance coverage.

• 401(k) retirement savings plan with company matching contributions.

• Company-provided WFH setup to ensure a productive remote work environment.

• Hybrid work environment, offering a balance between in-office collaboration and remote flexibility.

• Opportunity to contribute to a meaningful mission within a supportive and collaborative team culture.

Working Hours: Standard full-time hours, typically around 40 hours per week, with a hybrid schedule that likely involves a few days in the New York office and the remainder remote.

📝 Enhancement Note: The salary range provided is competitive for a Product Analyst role with 2-5 years of experience in New York City, especially considering the hybrid work model and comprehensive benefits. The emphasis on a "WFH setup" and "hybrid work environment" indicates a modern approach to employee support and work-life balance, which is attractive to operations professionals.

🎯 Team & Company Context

🏢 Company Culture

Industry: Insurtech (Insurance Technology). Afficiency operates within a regulated industry, requiring attention to detail, compliance, and robust processes, while leveraging technology to modernize and streamline life insurance purchasing.

Company Size: Rapidly growing, with a focus on scaling its proprietary platform and partnerships. This suggests an environment with evolving processes and opportunities for impact.

Founded: The founding date is not provided, but the company's mission to "shake up the life insurance industry" implies a forward-thinking, potentially disruptive culture focused on innovation and efficiency.

Team Structure:

• The Product Operations/Analytics team likely comprises individuals focused on user experience, data analysis, and process optimization.

• Reporting structure will likely be to a Product Lead, Head of Operations, or a similar management role overseeing GTM or product effectiveness.

• Cross-functional collaboration is essential, involving close partnerships with Product Management, Engineering, Design, Underwriting, and potentially Marketing and Sales teams to ensure a cohesive user journey and efficient operations. Methodology:

• Data-driven decision-making is paramount, using analytics from user behavior, conversion funnels, and support interactions to inform product and UX improvements.

• Agile methodologies are likely employed, focusing on iterative development, rapid prototyping, and continuous feedback loops.

• A strong emphasis on user-centric design and operational efficiency to streamline complex processes within the insurance industry.

Company Website: www.afficiency.com (inferred from domain_derived)

📝 Enhancement Note: The Insurtech context is critical. It implies a need for understanding compliance, data security, and the intricacies of financial services products. A "rapidly growing" company often means dynamic workflows and a chance for individuals to shape processes, which is a hallmark of successful operations professionals.

📈 Career & Growth Analysis

Operations Career Level: This role sits at an "Analyst" or "Associate" level, focusing on execution and hands-on problem-solving within product and user experience optimization. It's a critical role for driving incremental improvements that impact conversion and customer satisfaction.

Reporting Structure: The role will likely report to a Product Manager, Head of Product, or a Director of Operations/Revenue Operations, providing direct exposure to product strategy and operational execution.

Operations Impact: The role has a direct impact on revenue by improving conversion rates through UX optimization and reducing customer churn by addressing friction points. It also enhances operational efficiency by identifying and fixing workflow issues, potentially reducing support costs and underwriting exceptions.

Growth Opportunities:

• Specialization in Product Operations/UX Analytics: Deepen expertise in analyzing user behavior, leveraging AI tools for optimization, and mastering A/B testing and conversion rate optimization (CRO) techniques.

• Transition to Product Management: Develop a strong understanding of product strategy, user needs, and market dynamics, providing a solid foundation for moving into a Product Manager role.

• Leadership in Operations: Progress into roles with greater responsibility for defining operational strategies, managing cross-functional initiatives, and potentially leading a team focused on optimizing GTM or product operations.

📝 Enhancement Note: The growth path from this role is clear: it provides a strong foundation for specialized operations roles (Product Ops, RevOps) or a transition into Product Management. The emphasis on hands-on problem-solving and measurable impact makes this an attractive stepping stone for ambitious operations professionals.

🌐 Work Environment

Office Type: Hybrid work environment, indicating a blend of in-office collaboration and remote work flexibility.

Office Location(s): 175 Greenwich Street, New York, NY 10007, USA. This is a prime Manhattan location, suggesting a professional and accessible workspace.

Workspace Context:

• Collaborative Environment: The hybrid model suggests structured in-office days for team meetings, brainstorming sessions, and fostering strong working relationships with Product, Engineering, and other stakeholders.

• Tools & Technology: Access to modern collaboration tools, analytical software, and potentially dedicated AI platforms will be available to support the role's requirements.

• Team Interaction: Opportunities for direct interaction with product teams, engineers, and business stakeholders to gather context, present findings, and drive consensus on solutions.

Work Schedule: Standard full-time hours (approx. 40 hours/week) with a hybrid arrangement that offers flexibility. The specific in-office days will likely be determined by team needs and management direction.

📝 Enhancement Note: The New York City location, combined with a hybrid model, offers a balance of access to a major business hub and personal flexibility. This is appealing for professionals who value both networking opportunities and the ability to manage their work-life balance.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review applications and conduct an initial call to assess basic qualifications, experience, and cultural fit.

• Analytical/Case Study Interview: Expect a session focused on problem-solving and analytical skills. This may involve analyzing a hypothetical user journey, interpreting data, or discussing how you would approach a specific UX optimization challenge. Be prepared to discuss your thought process and how you'd leverage AI tools.

• Team/Stakeholder Interviews: Meetings with potential team members (e.g., Product Managers, Engineers) to evaluate collaboration style, communication effectiveness, and technical aptitude.

• Hiring Manager Interview: A final discussion focusing on overall fit, career aspirations, and a deeper dive into your experience and approach to ownership and execution.

Portfolio Review Tips:

• Focus on Impact: Clearly articulate the problem you solved, the solution you implemented (especially if AI-assisted), and the measurable results (e.g., % increase in conversion, % decrease in drop-off, time saved).

• Showcase AI Application: Highlight specific examples of how you used AI tools for prototyping, analysis, or automation. Detail the prompts used, the outputs generated, and how these outputs contributed to the final solution.

• Structure Your Narrative: For each case study, use a STAR (Situation, Task, Action, Result) or similar framework to present your contributions clearly and concisely.

• Tailor to Afficiency: Research Afficiency's products and mission. Frame your experience and portfolio examples to align with their goals of modernizing life insurance and optimizing digital journeys.

Challenge Preparation:

• Practice AI Prompting: Familiarize yourself with prompt engineering for AI tools like Claude, focusing on tasks relevant to analysis, content generation, and prototyping.

• Data Interpretation: Be ready to interpret sample data sets (e.g., funnel drop-offs, user session summaries) and propose actionable solutions.

• Business Judgment Scenarios: Prepare to discuss how you would prioritize competing issues, assess the business impact of a change, or make trade-offs.

• Communication Practice: Rehearse explaining complex technical or analytical concepts in simple terms to non-technical stakeholders.

📝 Enhancement Note: The emphasis on AI tools and direct implementation means interviewers will likely probe for practical examples. A portfolio demonstrating hands-on work with AI for tangible outcomes will be highly advantageous. Be ready to discuss your "ownership instinct" and how you've proactively solved problems.

🛠 Tools & Technology Stack

Primary Tools:

• AI Tools (e.g., Claude): Core to the role for prototyping, content generation, workflow adjustments, and potentially data analysis assistance. Proficiency in prompt engineering and leveraging these tools for speed and efficiency is key.

• Product Analytics Platforms: Tools for analyzing user behavior, session recordings, and conversion funnels (e.g., FullStory, Hotjar, Mixpanel, Amplitude).

• Collaboration Tools: Standard office suites and communication platforms (e.g., Google Workspace, Slack, Microsoft Teams).

Analytics & Reporting:

• Data Visualization Tools: Potentially Tableau, Power BI, or similar for creating dashboards and reports to track UX improvements and business impact.

• Spreadsheet Software: Advanced proficiency in Excel or Google Sheets for data manipulation and analysis.

CRM & Automation:

• While not explicitly mentioned, understanding CRM principles (e.g., Salesforce) and basic automation concepts will be beneficial given the GTM context of Insurtech. Familiarity with workflow automation principles is a plus.

• SQL (Preferred): Experience with SQL for direct data querying would be a significant advantage for deeper analysis.

📝 Enhancement Note: The explicit mention of "AI tools (Claude and others)" highlights this as a critical technical requirement. Candidates should be prepared to discuss their experience with AI in a practical, applied context for problem-solving and execution, not just theoretical knowledge.

👥 Team Culture & Values

Operations Values:

• Data-Driven Impact: Decisions and improvements are grounded in data analysis and measured by their tangible business outcomes.

• User-Centricity: A commitment to understanding and improving the customer experience at every touchpoint.

• Proactive Ownership: A culture where individuals take initiative to identify problems and drive solutions to completion.

• Efficiency & Automation: A continuous drive to streamline processes, reduce friction, and leverage technology (including AI) to work smarter.

• Collaboration & Communication: Openness to sharing insights, providing feedback, and working effectively across teams.

Collaboration Style:

• Cross-Functional Integration: A strong emphasis on working seamlessly with Product, Engineering, and Underwriting to ensure holistic solutions.

• Iterative Feedback: A willingness to share work-in-progress, receive constructive criticism, and iterate based on feedback.

• Knowledge Sharing: Encouraging the sharing of learnings, best practices, and successful strategies across the team and broader organization.

📝 Enhancement Note: The emphasis on "ownership instinct" and using AI to "fix it yourself" points to a culture that values proactivity, self-sufficiency, and hands-on contribution. This is a key aspect for operations roles that often require bridging gaps and driving initiatives independently.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating a Regulated Industry: Balancing user experience optimization with compliance requirements in the Insurtech space.

• Data Granularity: Ensuring access to and effective analysis of detailed user data across complex digital journeys.

• AI Tool Integration: Effectively integrating and scaling the use of AI tools into existing workflows and processes for maximum impact.

• Prioritization: Managing a backlog of potential improvements and effectively prioritizing based on business impact and feasibility.

Learning & Development Opportunities:

• Advanced AI Tool Mastery: Becoming an expert in leveraging AI for product analysis, prototyping, and automation within the Insurtech context.

• Product Analytics Specialization: Developing deep skills in user behavior analysis, A/B testing, and conversion rate optimization.

• Cross-Functional Exposure: Gaining a comprehensive understanding of product development, underwriting processes, and go-to-market strategies.

• Mentorship: Opportunities to learn from experienced product and operations professionals within a growing company.

📝 Enhancement Note: The challenges highlight the dynamic nature of the role, especially concerning AI integration and the regulated environment. The growth opportunities are well-defined, offering clear paths for skill development and career advancement within the operations and product domains.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you identified a significant user friction point and what steps you took to resolve it. How did you use data to support your decision, and what was the outcome?" (Focus on data, action, and measurable results).

• "How would you approach using AI tools like Claude to prototype a new feature or improve an existing user flow? Walk me through your thought process and potential outputs." (Demonstrate practical AI application and iterative thinking).

• "Imagine you've noticed a high drop-off rate in a specific part of our application. What is your step-by-step process for diagnosing the cause and proposing a solution?" (Showcase analytical rigor and problem-solving methodology). Company & Culture Questions:

• "Why are you interested in Afficiency and the Insurtech industry?" (Research Afficiency's mission, products, and market position).

• "How do you approach taking ownership of a problem, especially when it's outside your direct responsibilities?" (Highlight your proactive nature and "fix-it" mentality).

• "How do you balance the need for quick iteration and shipping improvements with ensuring the quality and accuracy required in a regulated industry?" (Demonstrate judgment and understanding of trade-offs). Portfolio Presentation Strategy:

• Quantify Everything: For each portfolio example, clearly state the problem, your specific actions (especially AI usage), and the quantifiable results achieved (e.g., conversion lift, time saved, error reduction).

• Show, Don't Just Tell: Be ready to walk through screenshots, mockups, or even brief demo recordings of your work, particularly highlighting AI-generated prototypes or process improvements.

• Focus on Process: Explain your methodology for identifying issues, analyzing data, using AI tools, implementing solutions, and measuring impact.

• Connect to Afficiency's Goals: Frame your experience and portfolio items in the context of how they align with Afficiency's mission to simplify life insurance and improve digital experiences.

📝 Enhancement Note: Interview preparation should heavily emphasize practical application of AI tools and demonstrating a proactive, ownership-driven approach. Be ready to discuss specific examples from your experience that showcase these capabilities, backed by data and measurable outcomes.

📌 Application Steps

To apply for this Product Analyst, AI & UX Optimization position:

• Submit your application: Complete the application form through the provided link on SmartRecruiters.

• Tailor your resume: Highlight experiences related to product analysis, UX optimization, data interpretation, AI tool usage, and process improvement. Quantify achievements wherever possible.

• Prepare your portfolio: Curate 2-3 strong case studies showcasing your ability to identify UX friction, leverage AI for solutions, and drive measurable improvements. Focus on tangible results and your process.

• Research Afficiency: Understand their mission, products, and the Insurtech landscape. Prepare to discuss how your skills align with their specific needs.

• Practice your pitch: Be ready to articulate your problem-solving approach, your experience with AI tools, and your commitment to ownership during interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.