Product Strategy Analyst - New Customers

📍 Job Overview

Job Title: Product Strategy Analyst - New Customers

Company: iwoca

Location: London, United Kingdom

Job Type: FULL_TIME

Category: Product Strategy / Commercial Analytics

Date Posted: October 1, 2026

Experience Level: Mid-Level (2-5 years)

Remote Status: Hybrid

🚀 Role Summary

• Define and execute the product strategy for new customer acquisition, focusing on optimizing the sign-up flow, documentation requirements, and funding decision models.

• Drive strategic initiatives by identifying drop-off points and commercial opportunities within the conversion funnel, with a primary focus on maximizing customer lifetime value (CLV).

• Design, implement, and analyze controlled experiments (e.g., A/B tests) to validate hypotheses and inform evidence-based decisions for product and policy enhancements.

• Manage analytical and strategic projects end-to-end, presenting findings and recommendations directly to senior leadership to influence business direction.

📝 Enhancement Note: This role bridges product strategy, commercial analytics, and data science within the new customer acquisition funnel for a fintech company. The emphasis on customer lifetime value, experimentation, and direct senior leadership engagement indicates a highly analytical and strategic position with significant business impact. The mention of AI leverage suggests a forward-thinking approach to analysis and workflow optimization.

📈 Primary Responsibilities

• Develop and refine the strategic roadmap for new customer onboarding, balancing speed, friction, risk, and decision accuracy.

• Identify and prioritize experiments and initiatives to address conversion funnel drop-offs and capture commercial opportunities, with a data-driven approach to ROI.

• Design and execute rigorous A/B tests and other controlled experiments to measure the impact of changes to the customer journey and loan features.

• Analyze experimental results using statistical methods to provide clear, actionable insights and recommendations for product and policy adjustments.

• Collaborate closely with data scientists, software engineers, and credit risk teams to translate analytical insights into production systems and operational processes.

• Proactively identify opportunities to leverage AI and machine learning for enhanced decision-making, process automation, and analytical insights within the new customer acquisition lifecycle.

• Prepare and deliver compelling presentations of findings, strategic recommendations, and project updates to senior management and cross-functional stakeholders.

• Contribute to the team's long-term roadmap planning, demonstrating potential for future leadership within the New Customers team.

📝 Enhancement Note: The responsibilities highlight a blend of strategic thinking, analytical rigor, and execution. The focus on "customer lifetime value as your key metric" suggests a deep dive into long-term business impact, moving beyond immediate conversion metrics. The expectation to "manage analytical and strategic projects end-to-end" and "partner with the Team Lead to shape the team's long-term roadmap" points to a role with significant ownership and potential for career advancement.

🎓 Skills & Qualifications

Education:

• Bachelor's degree in a STEM field (e.g., Mathematics, Statistics, Physics, Engineering) or equivalent practical experience. Experience:

• 2-5 years of professional experience in a strategy, commercial analytics, product management, finance, or consulting role, with a proven track record of using data to drive commercial decisions.

• Experience analyzing and optimizing customer journeys, with a focus on balancing conversion rates, risk, and long-term customer value.

• Demonstrated ability to design, run, and interpret controlled experiments (e.g., A/B tests) to inform product or policy decisions.

• Experience working collaboratively with engineering or data science teams to implement analytical insights into production systems. Required Skills:

• Commercial Analytics: Ability to translate data into actionable commercial insights related to revenue, cost, and risk for business stakeholders.

• Quantitative Foundations: Strong understanding of statistical principles, reasoning about uncertainty, and applying these to analytical problems.

• First-Principles Thinking: Aptitude for deconstructing complex problems into fundamental components and developing systematic solutions.

• Clear Communication: Excellent written and verbal communication skills, with the ability to tailor technical details to diverse audiences.

• AI Leverage: Proven experience building AI workflows or utilizing AI tools for analysis and prototyping, demonstrating judgment in AI application.

Preferred Skills:

• Experimentation Design: Hands-on experience with designing, implementing, and analyzing A/B tests and other experimental methodologies.

• Cross-functional Delivery: Experience in successfully delivering analytical projects in collaboration with engineering and data science teams.

• Customer Journey Analytics: Specific expertise in analyzing and optimizing customer acquisition funnels to enhance conversion and long-term value.

• Coding Abilities: Proficiency in a programming language (e.g., Python, R) for data analysis, automation, or prototyping, or demonstrated skill with AI coding assistants.

📝 Enhancement Note: The requirements emphasize a blend of analytical prowess, strategic thinking, and practical application. The "AI leverage" requirement, including building AI workflows or using AI for analysis, is a significant differentiator, indicating a modern approach to problem-solving. The bonus skills provide clear pathways for candidates to showcase relevant experience that will make them stand out.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies on Optimization: Showcase at least two detailed case studies demonstrating your ability to analyze a complex problem, propose a data-driven solution, and measure its impact. Focus on initiatives that improved commercial outcomes (e.g., increased conversion, reduced risk, enhanced CLV).

• Experimentation Design & Analysis: Include examples of experiments you designed and analyzed, clearly outlining the hypothesis, methodology, statistical significance, and business impact. Highlight your approach to interpreting results and making recommendations.

• Customer Journey Improvement: Present a project where you analyzed a customer journey, identified friction points or opportunities, and implemented changes that led to measurable improvements in key metrics.

• Cross-functional Collaboration Examples: Detail instances where you collaborated with technical teams (engineering, data science) to implement analytical solutions or product changes, showcasing your ability to bridge the gap between analysis and production.

Process Documentation:

• Problem Definition & Hypothesis Formulation: Demonstrate how you systematically define problems, formulate testable hypotheses, and outline the analytical approach.

• Data Analysis & Interpretation: Provide examples of your data analysis techniques, statistical reasoning, and ability to interpret complex datasets to derive actionable insights.

• Experimentation Methodology: Show your understanding of experimental design principles, including sample size calculation, statistical testing, and potential biases.

• Recommendation & Impact Reporting: Illustrate how you communicate findings and recommendations clearly to stakeholders, and how you track and report on the realized business impact of implemented solutions.

📝 Enhancement Note: For a role focused on product strategy and commercial analytics, a portfolio demonstrating strategic thinking, analytical rigor, and measurable impact is crucial. The emphasis should be on how you use data and experimentation to drive business outcomes, particularly within a customer acquisition context. Showcasing collaboration with technical teams and the ability to translate insights into production is key.

💵 Compensation & Benefits

Salary Range: £60,000 - £80,000 per annum.

Benefits:

• Comprehensive Medical Coverage: Medical insurance from Vitality, including discounted gym membership.

• Convenient Healthcare Access: Private GP service for employees, partners, and dependents.

• Generous Paid Time Off: 25 days of holiday per year, plus an extra day for your birthday.

• Flexible Leave Options: Option to buy or sell up to five additional days of annual leave, and unlimited unpaid leave.

• Long-Term Service Recognition: A one-month, fully paid sabbatical after four years of employment.

• Mental Health Support: Instant access to external counseling and therapy sessions.

• Retirement Savings: 3% Pension contributions on total earnings.

• Equity Ownership: Employee equity incentive scheme, aligning your success with the company's.

• Family Support: Generous parental leave and a nursery tax benefit scheme.

• Sustainable Commuting: Electric car scheme and cycle to work scheme.

• Team Engagement: Two company retreats per year for team building and networking.

• Continuous Learning: A dedicated learning and development budget for professional growth.

• Knowledge Sharing: Access to company-wide talks and learning platforms like Treehouse.

Working Hours:

• Flexible working hours, supporting a hybrid work arrangement.

• Standard full-time hours are assumed to be around 40 hours per week, with flexibility to manage workload effectively.

📝 Enhancement Note: The salary range is competitive for a mid-level Product Strategy Analyst in London. The benefits package is extensive, covering health, well-being, work-life balance, professional development, and financial incentives, which are highly attractive for operations and strategy professionals. The mention of flexible working hours aligns with modern work expectations.

🎯 Team & Company Context

🏢 Company Culture

Industry: Fintech (SME Lending)

Company Size: iwoca is a growing fintech company, indicated by its broad range of benefits and focus on structured career development, suggesting it's beyond a startup phase but still agile. The company operates internationally with offices in multiple European cities.

Founded: iwoca was founded with the mission to provide fast, flexible finance to SMEs, indicating a core value of supporting small businesses and fostering economic growth.

Team Structure:

• New Customers Team: This is a cross-functional team comprising data scientists, analysts, and software engineers.

• Reporting Structure: The role reports into a Team Lead within the New Customers team, with direct interaction and reporting of findings to senior leadership.

• Collaboration: Strong emphasis on knowledge sharing through regular forums and dedicated R&D time. Close partnership with the credit risk function is essential.

Methodology:

• Data-Driven Decisions: The company culture champions evidence-based decision-making, heavily relying on data analysis and statistical rigor.

• Experimentation: A core part of the team's workflow involves designing, running, and interpreting controlled experiments to drive product and strategy evolution.

• AI Integration: iwoca actively embraces AI, providing tools and data access to leverage AI for faster and better work, emphasizing continuous learning and adaptation.

Company Website: https://www.iwoca.co.uk/

📝 Enhancement Note: The company culture is described as one where "the best idea wins," emphasizing independent thinking, challenging assumptions, and evidence-based decision-making. The strong focus on AI and continuous learning is a key differentiator. The "New Customers" team structure suggests a dedicated unit focused on a critical part of the business lifecycle, fostering deep expertise.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a mid-level Product Strategy Analyst, suitable for individuals with 2-5 years of experience. It offers significant autonomy and responsibility, managing projects end-to-end and presenting to senior leadership.

Reporting Structure: The analyst will report to the New Customers Team Lead. This structure provides mentorship and guidance while allowing for direct exposure to senior decision-makers.

Operations Impact: The role has a direct impact on business growth by shaping the customer acquisition strategy. Success is measured by key metrics like customer lifetime value, conversion rates, and overall commercial outcomes, demonstrating the strategic importance of this position within iwoca's GTM operations.

Growth Opportunities:

• Team Lead Progression: The role explicitly states the expectation of growing into a Team Lead role, providing a clear leadership development path within the New Customers team.

• Skill Specialization: Opportunities to deepen expertise in areas such as advanced experimentation, AI-driven product strategy, and customer journey optimization.

• Cross-Functional Exposure: Collaboration with data science, engineering, and credit risk teams offers broad exposure to different facets of the fintech business, enhancing overall business acumen.

• Strategic Influence: Direct involvement in shaping company-wide lending strategy for new customers provides a platform for significant strategic influence and visibility.

📝 Enhancement Note: The explicit mention of growing into a Team Lead role is a significant career growth indicator. The role's focus on experimentation, AI, and customer lifetime value provides opportunities to develop highly sought-after skills in the operations and product strategy domain.

🌐 Work Environment

Office Type: Hybrid work model, with employees expected to work from the London office. This suggests a blend of remote flexibility and in-office collaboration.

Office Location(s): Offices located in London, Leeds, Berlin, and Frankfurt. The specific role is based in London.

Workspace Context:

• Collaborative Hub: The London office is described as a place with "plenty of drinks and snacks," and hosts social events and community groups, fostering a vibrant and connected atmosphere conducive to collaboration.

• Technology Enabled: As a tech company, iwoca likely provides access to modern tools and infrastructure, including AI models and data platforms, supporting analytical and strategic work.

• Team Interaction: The hybrid model and emphasis on team structure within the New Customers team suggest regular opportunities for interaction with colleagues, fostering knowledge sharing and team cohesion.

Work Schedule:

• Offers flexible working hours, allowing employees to manage their schedules effectively within a full-time capacity. This flexibility is beneficial for deep analytical work and balancing personal commitments.

📝 Enhancement Note: The hybrid model in London combines the benefits of remote work with the advantages of in-person collaboration and company culture immersion. The description of the office environment and social activities points to a company that values employee engagement and community.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your application, focusing on your CV and any portfolio materials submitted, assessing your alignment with the essential requirements.

• Analytical/Strategy Challenge: Expect a practical exercise or case study designed to evaluate your commercial analytics, problem-solving, and experimentation skills. This may involve analyzing a dataset or a business scenario related to customer acquisition.

• Team/Hiring Manager Interviews: Discussions to assess your technical skills, strategic thinking, communication style, and cultural fit with the New Customers team and iwoca's values. You'll likely discuss your approach to experimentation and AI leverage.

• Senior Leadership Interview: A final conversation to evaluate your strategic vision, leadership potential, and overall impact on the business. This is where your ability to present complex ideas clearly to senior stakeholders will be key.

Portfolio Review Tips:

• Highlight Impact: For each case study, clearly articulate the problem, your analytical approach, the specific actions taken, and the quantifiable business impact (e.g., % increase in conversion, reduction in drop-off, projected CLV uplift).

• Showcase Process: Detail your methodology for problem decomposition, hypothesis generation, experiment design (including statistical considerations), and data analysis.

• Demonstrate Strategic Thinking: Explain how your analysis and recommendations align with broader business goals and how you weighed trade-offs (e.g., speed vs. risk).

• AI Integration Examples: If applicable, showcase how you've used AI or advanced analytical tools to enhance your work, explaining the specific benefits and outcomes.

• Tailor to Role: Emphasize projects related to customer journeys, conversion funnels, and lending strategy, as these are core to the role.

Challenge Preparation:

• Understand the Business: Research iwoca's business model, target market (SMEs), and competitive landscape in the fintech lending space.

• Practice Experimentation: Be ready to discuss experimental design principles, common pitfalls, and how to interpret results, especially A/B tests.

• Commercial Acumen: Prepare to discuss how you would approach identifying commercial opportunities and optimizing metrics like conversion rate and customer lifetime value.

• AI Application: Think about how AI can be applied to customer acquisition, risk assessment, or process automation within a lending context.

• Communication Clarity: Practice articulating complex analytical concepts and strategic recommendations concisely and persuasively.

📝 Enhancement Note: The interview process is designed to rigorously assess analytical, strategic, and communication skills. A strong portfolio is essential, and candidates should be prepared to discuss their experience with experimentation, AI, and driving business impact through data. The "TAP" interview welcome pack link suggests the company provides resources to help candidates prepare.

🛠 Tools & Technology Stack

Primary Tools:

• Data Analysis & Manipulation: Proficiency in tools for data extraction, transformation, and analysis. This would likely include SQL for querying databases and potentially Python or R for more advanced statistical analysis and scripting.

• Experimentation Platforms: Experience with A/B testing tools or frameworks for designing, deploying, and analyzing controlled experiments.

• AI & ML Tools: Familiarity with leveraging AI models for analysis, prototyping, or workflow automation. This could include platforms like Claude Code or other generative AI tools, as well as understanding how to integrate ML models into decision-making processes.

Analytics & Reporting:

• Business Intelligence (BI) Tools: Experience with BI platforms (e.g., Tableau, Looker, Power BI) for creating dashboards, visualizing data, and communicating insights to stakeholders.

• Web Analytics: Understanding of tools like Google Analytics or similar platforms for tracking user behavior on websites and optimizing conversion funnels.

• Statistical Software: Familiarity with statistical packages or libraries (e.g., SciPy, Statsmodels in Python; base R or specific R packages) for rigorous quantitative analysis.

CRM & Automation:

• CRM Systems: While not explicitly mentioned, familiarity with CRM systems (e.g., Salesforce) is often beneficial for understanding customer data flow and sales processes, though less critical for this specific product strategy role.

• Workflow Automation: Understanding of how to automate processes, particularly through scripting or integration tools, to improve efficiency in data analysis or operational workflows.

📝 Enhancement Note: The role heavily emphasizes analytical and experimental capabilities. While specific tools aren't listed, a strong foundation in SQL, statistical analysis (likely Python/R), and experimentation platforms is expected. The explicit mention of AI leverage suggests familiarity with current AI tools for analysis and coding.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decisions: A fundamental value at iwoca, meaning all strategic and operational decisions are grounded in rigorous data analysis and evidence.

• Challenging Assumptions: The culture encourages independent thinking and questioning untested logic to ensure robust decision-making and continuous improvement.

• Learning and Growth: A strong emphasis on personal and professional development, providing autonomy for individuals to grow in directions that maximize their effectiveness and contribution.

• AI Leverage for Efficiency: Embracing AI as a tool to work faster and better, fostering an environment of continuous learning and adaptation to new technologies.

• Customer Centricity: While focused on new customers, the underlying goal is to support SMEs, indicating a value placed on customer success and impact.

Collaboration Style:

• Cross-functional Integration: The New Customers team is inherently cross-functional, requiring seamless collaboration between analysts, data scientists, and engineers.

• Knowledge Sharing: A culture of open knowledge sharing through regular forums and dedicated R&D time promotes collective learning and problem-solving.

• Evidence-Based Dialogue: Discussions are expected to be constructive, focusing on evidence and data to support arguments and reach optimal solutions.

• Partnership with Risk: Close collaboration with the credit risk team is vital for balancing growth objectives with prudent lending practices.

📝 Enhancement Note: The culture is built on intellectual curiosity, rigorous analysis, and a forward-thinking approach to technology (AI). The emphasis on "the best idea wins" fosters an environment where innovative solutions are valued, provided they are backed by evidence.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Competing Objectives: Navigating the trade-offs between speed of acquisition, customer friction, risk appetite, and decision accuracy requires sophisticated strategic judgment.

• Data Complexity and Interpretation: Working with diverse datasets and ensuring accurate interpretation to drive impactful decisions, especially when dealing with uncertainty and calibration.

• Translating Insights into Production: Effectively collaborating with engineering teams to ensure analytical insights and experimental results are correctly implemented in live systems.

• Staying Ahead of AI Advancements: Continuously learning and adapting to the rapidly evolving AI landscape to leverage new tools and techniques effectively for analysis and productivity.

Learning & Development Opportunities:

• Advanced Experimentation: Deepen expertise in experimental design, statistical analysis, and causal inference to drive more sophisticated product and policy testing.

• AI & Machine Learning Applications: Gain hands-on experience applying AI and ML techniques to product strategy, risk modeling, and process automation within a financial services context.

• Strategic Leadership: Develop leadership capabilities through managing projects, mentoring junior team members (as you grow into a lead role), and influencing senior stakeholders.

• Fintech Industry Acumen: Build comprehensive knowledge of the SME lending market, regulatory environment, and competitive dynamics in the fintech sector.

📝 Enhancement Note: The challenges are inherent to a fast-paced, data-intensive environment like fintech. The growth opportunities are substantial, particularly in developing highly in-demand skills in AI, experimentation, and strategic leadership within the financial services industry.

💡 Interview Preparation

Strategy Questions:

• "How would you approach defining the lending strategy for new customers, considering the trade-offs between speed, friction, risk, and decision accuracy?" (Prepare to discuss frameworks, prioritization methods, and data sources.)

• "Describe a time you identified a significant commercial opportunity or drop-off point in a customer journey. What was your analysis, and what initiatives did you propose or implement?" (Focus on quantifiable results and your strategic reasoning.)

• "Imagine we are considering a change to our application process that could increase conversion by 5% but might slightly increase risk. How would you design an experiment to evaluate this, and what factors would you consider in your recommendation?" (Highlight your understanding of experimental design, statistical significance, and risk assessment.) Company & Culture Questions:

• "How do you see AI being leveraged to improve the new customer acquisition process at iwoca?" (Showcase your understanding of AI's practical applications in this domain.)

• "Describe your experience working in a cross-functional team. How do you ensure effective collaboration and knowledge sharing?" (Emphasize your communication and teamwork skills, and how you navigate diverse perspectives.)

• "How do you approach challenging untested logic or assumptions within a team?" (Demonstrate your ability to engage constructively and use data to support your arguments.) Portfolio Presentation Strategy:

• Structure for Impact: Organize your portfolio around key achievements, using the STAR method (Situation, Task, Action, Result) or a similar framework for each case study.

• Quantify Everything: For each project, clearly state the problem, your specific contribution, the actions you took, and the measurable business outcomes (e.g., % improvements, cost savings, revenue impact).

• Highlight Strategic Thinking: Explain why you chose a particular approach, how you considered trade-offs, and how your work aligned with broader business objectives.

• Showcase Process: Be ready to walk through your analytical process, from problem definition and data gathering to analysis, experimentation, and recommendation.

• Concise Storytelling: Present your work clearly and concisely, focusing on the most impactful elements. Be prepared to answer detailed questions about your methodology and results.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong grasp of commercial analytics, experimental design, strategic thinking, and the ability to leverage AI. Candidates should be ready to articulate their impact with specific, quantified results and showcase their process for problem-solving.

📌 Application Steps

To apply for this Product Strategy Analyst position:

• Submit your application through the provided link on Ashby.

• Customize Your Resume: Tailor your resume to highlight experience in commercial analytics, product strategy, experimentation, and AI leverage. Use keywords from the job description and quantify your achievements with specific metrics and business impact.

• Prepare Your Portfolio: Curate 2-3 strong case studies that showcase your ability to analyze complex problems, design and execute experiments, drive commercial outcomes, and collaborate with technical teams. Ensure each case study clearly articulates the problem, your role, the methodology, and the quantified results.

• Research iwoca: Understand iwoca's business model, target market (SMEs), and its position in the fintech lending space. Familiarize yourself with its culture, values, and recent news.

• Practice Interview Questions: Prepare to answer strategy, analytical, and behavioral questions, focusing on your experience with A/B testing, customer journey optimization, AI application, and cross-functional collaboration. Practice presenting your portfolio projects concisely and impactfully.

⚠️ 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.