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

Date Posted: August 13, 2026

Experience Level: 2-5 Years

Remote Status: Hybrid

🚀 Role Summary

• This role is a unique hybrid of product analysis and hands-on execution, focusing on optimizing user experience (UX) and workflows within an Insurtech platform.

• You will leverage AI tools, specifically mentioning Claude, to identify, prototype, and implement improvements to application journeys, agent tools, and consumer-facing experiences.

• The core function is to act as a detective within the product, uncovering friction points and translating these insights into measurable, shipped enhancements rather than just documentation.

• Success is defined by a track record of independently driving impactful UX and workflow improvements from identification through to implementation and validation.

📝 Enhancement Note: This role bridges traditional product analysis with a strong operational execution component, requiring a blend of analytical rigor and proactive problem-solving. The emphasis on using AI tools for prototyping and direct implementation differentiates it from standard analyst roles, leaning heavily into operational efficiency and rapid iteration.

📈 Primary Responsibilities

• Conduct in-depth reviews of Afficiency's product interfaces, including application flows, agent portals, and consumer-facing experiences, to pinpoint areas of user confusion, friction, and drop-off.

• Analyze real-world user data, including session recordings, support tickets, underwriting outcomes, and conversion funnel metrics, to diagnose product performance issues and identify root causes of user frustration.

• Develop concrete, actionable recommendations for product and UX improvements, grounded in demonstrable business impact and user experience best practices, moving beyond subjective observations.

• Utilize AI tools, such as Claude, to actively prototype, build, or directly implement solutions, including copy adjustments, flow optimizations, minor tooling enhancements, automation scripts, or reporting dashboards.

• Collaborate closely with product management, engineering, and underwriting teams to scope, prioritize, and execute changes, escalating complex technical requirements when necessary.

• Establish and maintain a rigorous process for measuring the effectiveness of implemented changes, tracking key performance indicators (KPIs), and iterating on solutions based on post-launch performance data.

• Apply sound business judgment and a customer-centric perspective to evaluate the feasibility and impact of proposed improvements, ensuring alignment with company objectives and user needs.

📝 Enhancement Note: The responsibilities highlight a "builder" mentality, moving beyond reporting to direct implementation. This suggests a need for individuals who are comfortable with ambiguity, can quickly iterate on solutions, and possess a strong sense of ownership over the entire problem-solving lifecycle.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a background in business, analytics, operations, or a related field is preferred, indicating a focus on practical application over formal academic credentials.

Experience: Approximately 2+ years of experience in business analysis, operations, product management, or a closely related function where analytical and problem-solving skills were paramount.

Required Skills:

• Proven analytical capabilities with a knack for identifying inconsistencies and understanding underlying causes in complex systems.

• Strong common sense and business acumen, with the ability to intuitively grasp how products and processes should function and to recognize where they fall short.

• Demonstrated self-starter mentality and proactive approach to problem identification and resolution; ability to operate with minimal direct supervision.

• A pronounced sense of ownership and a drive to directly address and resolve issues rather than deferring them.

• Proficiency and willingness to learn and utilize AI tools (e.g., Claude) for analysis, prototyping, and direct implementation of solutions.

• Excellent written and verbal communication skills, with the ability to articulate complex issues and solutions clearly to diverse audiences, including technical and non-technical stakeholders. Preferred Skills:

• Prior experience within the insurance, fintech, or other heavily regulated industries, understanding the nuances of complex product environments.

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

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

• Demonstrated hands-on experience using AI tools for practical application, such as building workflows, automations, or prototypes, even in an informal capacity.

📝 Enhancement Note: The emphasis on "non-technical background is completely fine" alongside the preference for AI tool proficiency suggests that adaptability, analytical thinking, and a proactive "can-do" attitude are prioritized over specific technical degrees or extensive coding experience.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase examples of identifying and diagnosing user friction points within digital products or complex workflows.

• Present case studies demonstrating how you translated analytical findings into concrete, actionable solutions.

• Include examples where you utilized data to measure the impact of implemented changes and iterated based on results.

• Demonstrate instances where you leveraged technology or tools (including AI if applicable) to accelerate analysis or implementation. Process Documentation:

• Provide evidence of your ability to document user journeys and identify key process bottlenecks.

• Illustrate your approach to designing or refining workflows for improved efficiency and user experience.

• Showcase how you have measured and reported on the performance of processes you have optimized.

📝 Enhancement Note: Given the role's emphasis on hands-on execution and AI tool usage, a portfolio should highlight tangible outcomes and the process of getting there. This includes demonstrating the analytical steps, the creative problem-solving, the specific tools used (especially AI), and the measurable impact of the implemented solutions.

💵 Compensation & Benefits

Salary Range: $80,000 – $105,000 USD per year, commensurate with experience and qualifications.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

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

• Stipend or provision for a company-paid work-from-home setup to ensure an optimal remote work environment.

• Hybrid work environment fostering collaboration and 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. The hybrid nature of the role allows for flexibility in scheduling, balancing in-office collaboration with remote work.

📝 Enhancement Note: The salary range provided is specific to the New York City metropolitan area for a role with 2-5 years of experience in product analysis and operations, considering the company's industry (Insurtech) and the hybrid work arrangement. This range aligns with industry benchmarks for similar positions in high-cost-of-living urban centers.

🎯 Team & Company Context

🏢 Company Culture

Industry: Insurtech (Insurance Technology), specifically focused on modernizing life insurance distribution and underwriting through digital platforms. This industry is characterized by complex regulatory environments, a need for robust data security, and a drive towards digital transformation.

Company Size: Afficiency is described as "rapidly growing," suggesting a dynamic startup environment. This typically means opportunities for significant impact, cross-functional collaboration, and a culture that values agility and innovation.

Founded: The founding date is not specified, but the description implies a relatively established presence with proprietary platforms and partnerships, suggesting it's beyond the very early startup phase but still in a growth trajectory.

Team Structure:

• The Product Operations/Analyst team likely operates within or in close collaboration with Product Management and Engineering.

• Reporting structure will likely be to a Product Manager, Head of Product, or Operations Lead, with direct interaction across engineering, underwriting, and customer support.

• Cross-functional collaboration is a core tenet of this role, requiring constant engagement with various departments to identify issues and implement solutions. Methodology:

• Data-driven decision-making is central, using session recordings, support tickets, and funnel data to inform UX and product improvements.

• Iterative development and continuous improvement are key, with an emphasis on shipping changes and measuring their impact.

• AI-assisted workflows are encouraged to drive efficiency and speed up the analysis and implementation cycles.

Company Website: afficiency.com (Inferred from domain_derived)

📝 Enhancement Note: A "rapidly growing Insurtech company" implies a fast-paced environment where individuals can make a tangible impact. The culture likely values proactivity, data-informed decisions, and a willingness to embrace new technologies like AI to drive efficiency.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as an Analyst, suitable for individuals with 2-5 years of experience. It offers a blend of analytical work and hands-on implementation, acting as a crucial link between identifying user pain points and driving tangible product improvements. It's an excellent stepping stone for those looking to deepen their product sense and operational execution skills.

Reporting Structure: The Product Analyst will likely report into a Product Management function or a dedicated Operations leadership role. They will work closely with Product Managers, Engineers, UX Designers, and Underwriting teams, requiring strong collaboration and communication skills.

Operations Impact: The role has a direct impact on revenue and user experience by identifying and resolving friction points that lead to application drop-offs, user frustration, and inefficient workflows. By improving these areas, the analyst contributes directly to conversion rates, customer satisfaction, and operational efficiency within the Insurtech platform.

Growth Opportunities:

• Specialization in AI-driven Product Optimization: Deepen expertise in leveraging AI tools for UX analysis, prototyping, and workflow automation within regulated industries.

• Product Management Track: Transition into a Product Manager role by demonstrating strategic thinking, cross-functional leadership, and a deep understanding of user needs and business impact.

• Operations Leadership: Grow into a more senior operations role, managing teams or specific operational functions focused on process improvement, system implementation, and efficiency gains.

• Industry Expertise: Develop specialized knowledge in Insurtech, fintech, and complex regulated product environments, becoming a subject matter expert.

📝 Enhancement Note: This role offers a unique blend of analytical and execution-focused growth. The emphasis on AI and direct implementation provides a modern skill set that is highly valuable. The potential to move into Product Management or specialized Operations leadership roles is significant, especially within a growing Insurtech company.

🌐 Work Environment

Office Type: Hybrid work environment, indicating a blend of in-office collaboration and remote work flexibility. This suggests a modern approach to workplace structure, balancing team cohesion with individual work preferences.

Office Location(s): The role is based in New York, NY, with a physical office at 175 Greenwich Street, New York, NY 10007. This prime Manhattan location offers accessibility and a vibrant professional ecosystem.

Workspace Context:

• The hybrid model likely fosters a collaborative atmosphere during in-office days, encouraging team interaction and spontaneous problem-solving.

• Access to necessary tools and technology is expected, including potentially advanced AI platforms and analytics software, supported by a company-paid WFH setup.

• Opportunities for direct interaction with product, engineering, and underwriting teams will be frequent, facilitating a deep understanding of the business and its challenges.

Work Schedule: The standard work schedule is likely 40 hours per week, with flexibility afforded by the hybrid arrangement. This allows operations professionals to manage their time effectively, balancing analytical deep work with collaborative team activities.

📝 Enhancement Note: The hybrid model in a major city like New York suggests a professional environment that values both collaboration and individual productivity. The "company-paid WFH setup" indicates a commitment to employee well-being and productivity regardless of location.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and any provided portfolio to assess qualifications and alignment with the role's requirements, focusing on analytical skills, ownership, and AI tool familiarity.

• Hiring Manager Interview: Discussion focused on your experience, problem-solving approach, understanding of UX/UI optimization, and how you've used data and tools (including AI) to drive improvements. Expect behavioral questions.

• Skills/Case Study Assessment: A practical exercise, potentially involving analyzing a product flow, identifying issues, and outlining potential AI-assisted solutions or a presentation of your portfolio showcasing past work.

• Team/Stakeholder Interviews: Meetings with potential peers and cross-functional collaborators (e.g., Product, Engineering) to assess cultural fit, communication style, and collaboration capabilities.

• Final Interview: A discussion with senior leadership to confirm fit, strategic alignment, and overall potential impact.

Portfolio Review Tips:

• Highlight AI Integration: Clearly showcase any projects where you used AI tools (like Claude) for analysis, prototyping, or implementation. Detail the specific AI capabilities you leveraged and the outcomes.

• Focus on Impact & Metrics: For each project, emphasize the problem identified, the solution implemented, and the measurable results (e.g., reduced drop-off rates, improved conversion, increased efficiency). Quantify your contributions.

• Demonstrate Ownership: Select projects where you took initiative, drove the process end-to-end, and solved problems proactively.

• Structure for Clarity: Organize your portfolio logically, perhaps by project type or impact area. For case studies, use a clear structure: Problem -> Analysis -> Solution (including tools used) -> Results -> Learnings.

• Tailor to the Role: Emphasize examples related to UX/UI optimization, workflow analysis, and process improvement within digital products, ideally in complex or regulated environments.

Challenge Preparation:

• Be ready to walk through a product or user journey and identify potential areas for AI-assisted UX optimization.

• Prepare to discuss how you would use session recordings, funnel data, and support tickets to diagnose issues.

• Think about how you would communicate complex findings and proposed solutions to both technical and non-technical stakeholders.

• Practice articulating the business value and ROI of your proposed improvements.

📝 Enhancement Note: The emphasis on AI tools and hands-on execution means your portfolio and interview responses should demonstrate not just analytical thinking but also a proactive, problem-solving bias with tangible outputs. Be prepared to discuss how you'd use AI to accelerate your work.

🛠 Tools & Technology Stack

Primary Tools:

• AI Tools: Explicit mention of Claude, indicating a need for proficiency in leveraging large language models for tasks such as content generation, data summarization, prototyping, and workflow automation.

• Session Replay Tools: (e.g., Hotjar, FullStory, LogRocket) for analyzing user behavior and identifying UX friction points.

• Funnel/Behavioral Analytics Tools: (e.g., Mixpanel, Amplitude, Google Analytics) for tracking user journeys and conversion rates.

Analytics & Reporting:

• Data Analysis Tools: Proficiency in interpreting data from various sources is key. While SQL is preferred, strong analytical skills with other tools may suffice.

• Reporting & Dashboarding Tools: Ability to create clear reports and dashboards to communicate findings and measure impact, potentially using tools integrated with analytics platforms.

CRM & Automation:

• CRM Systems: While not explicitly mentioned, familiarity with CRM platforms (e.g., Salesforce) is often beneficial for understanding customer journeys and sales-related workflows, especially in a B2B context like agent tools.

• Workflow Automation: Experience or aptitude for using tools to automate repetitive tasks and optimize processes.

📝 Enhancement Note: The specific mention of "Claude" and the general emphasis on AI tools suggest a forward-thinking approach to technology adoption. Candidates should be prepared to discuss their experience with generative AI and how they see it applied in product analysis and optimization.

👥 Team Culture & Values

Operations Values:

• Excellence and Impact: A drive to not just identify problems but to implement solutions that have a measurable positive impact on the product and business.

• Curiosity and Learning: A commitment to understanding user behavior, exploring new tools (especially AI), and continuously improving processes and skills.

• Ownership and Accountability: Taking personal responsibility for driving initiatives from start to finish and seeing them through to successful completion.

• Collaboration and Support: Working effectively with cross-functional teams and fostering a supportive environment where ideas are shared and challenges are tackled together.

• Customer-Centricity: Always prioritizing the user experience and ensuring that product and process improvements benefit the end-user (both agents and consumers).

Collaboration Style:

• Proactive and Cross-Functional: Actively engaging with Product, Engineering, and Underwriting to gather insights, share findings, and collaborate on solutions.

• Data-Informed Dialogue: Using data and clear analysis to drive discussions and influence decisions, ensuring that recommendations are well-substantiated.

• Iterative Feedback Loops: Embracing a culture of continuous feedback, where proposed solutions are discussed, refined, and iterated upon based on input from various stakeholders.

📝 Enhancement Note: The company culture appears to value proactivity, a results-oriented mindset, and a willingness to embrace new technologies. The emphasis on "ownership" and "not just writing it up and handing it off" suggests a team that rewards initiative and tangible contributions.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Analysis with Execution: The dual nature of the role requires shifting between deep analytical thinking and hands-on implementation, which can be demanding.

• Navigating Complex Workflows: Understanding and optimizing intricate insurance application and underwriting processes requires significant learning and attention to detail.

• Measuring AI Impact: Quantifying the precise business impact of AI-driven improvements can sometimes be challenging and require robust tracking mechanisms.

• Adapting to Rapid Growth: As a fast-growing company, processes and priorities may evolve quickly, requiring flexibility and adaptability.

Learning & Development Opportunities:

• AI Tool Mastery: Becoming highly proficient in using advanced AI tools for product analysis, prototyping, and automation, positioning yourself at the forefront of this technological wave.

• Insurtech Domain Expertise: Developing deep knowledge of the life insurance industry, its products, regulations, and operational nuances.

• Product Lifecycle Exposure: Gaining comprehensive experience across the entire product development and optimization lifecycle, from identification to implementation and measurement.

• Cross-Functional Leadership: Enhancing skills in stakeholder management, communication, and influencing across diverse teams, preparing for leadership roles.

📝 Enhancement Note: The challenges presented are common in dynamic, growth-oriented tech companies, particularly those integrating cutting-edge technology like AI. The growth opportunities are substantial, offering a path to specialized expertise and leadership.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you identified a significant user pain point in a product or workflow. How did you diagnose it, what was your proposed solution, and what was the outcome?" (Focus on your analytical process, data used, and ownership).

• "How would you use AI tools like Claude to improve the user experience of an insurance application process?" (Be ready to discuss specific AI applications for analysis, content generation, or workflow streamlining).

• "Walk us through a process you've optimized. What were the key metrics you tracked, and how did you measure success?" (Emphasize your process improvement methodology and data-driven validation). Company & Culture Questions:

• "What interests you about Afficiency and the Insurtech industry?" (Research Afficiency's mission, products, and recent news. Connect your skills to their goals).

• "How do you approach collaborating with engineering and product teams on implementing changes?" (Highlight your communication style, ability to influence, and focus on shared goals).

• "Describe a situation where you had to make a recommendation with incomplete data. How did you proceed?" (Showcase your business judgment and ability to make informed decisions under ambiguity). Portfolio Presentation Strategy:

• Start with the "Why": Clearly articulate the problem you were trying to solve and the business or user impact you aimed for.

• Show, Don't Just Tell: Use visuals (screenshots, flow diagrams) to illustrate the "before" and "after" of your improvements.

• Detail Your Process: Explain your analytical steps, the tools you used (especially AI), and how you arrived at your solution.

• Quantify Results: Present metrics clearly to demonstrate the tangible outcomes of your work. Be prepared to discuss ROI.

• Highlight AI's Role: Specifically point out where and how AI tools contributed to your efficiency or the effectiveness of the solution.

📝 Enhancement Note: Be prepared to discuss your understanding of AI's role in product optimization and operations. Demonstrating a proactive, hands-on approach and a clear ability to translate data into actionable, implemented improvements will be key.

📌 Application Steps

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

• Submit your application directly through the provided SmartRecruiters link.

• Customize your Resume: Highlight experience in product analysis, UX optimization, data interpretation, and any use of AI tools. Quantify achievements with metrics where possible, aligning with the 2+ years of experience requirement.

• Prepare Your Portfolio: Curate 2-3 key projects that showcase your analytical skills, problem-solving approach, and tangible results. Ensure you can clearly articulate the problem, your process (including AI usage), and the measurable impact.

• Research Afficiency: Understand their mission, platform, and target market (Insurtech). Be ready to articulate why you are a good fit for their growth-stage environment and their focus on AI-driven innovation.

• Practice Your Pitch: Be prepared to walk through your portfolio and answer behavioral and situational questions that assess your ownership, analytical rigor, and collaboration skills.

⚠️ 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.