Product Strategy Analyst - New Applications Team

📍 Job Overview

Job Title: Product Strategy Analyst - New Applications Team

Company: iwoca

Location: London, United Kingdom

Job Type: Full-Time

Category: Product Strategy & Analytics / Revenue Operations Support

Date Posted: February 26, 2026

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

Remote Status: Hybrid

🚀 Role Summary

• Drive strategic initiatives within the New Applications team, focusing on optimizing the customer journey from initial interest to loan offer.

• Leverage data analysis, structured experimentation, and commercial acumen to influence key decisions related to conversion, risk assessment, and customer lifetime value.

• Develop and refine lending strategies and customer assessment processes, balancing speed, accuracy, and customer friction.

• Collaborate cross-functionally with Engineering, Design, and Data Science teams to translate insights into actionable product and process improvements.

• Utilize SQL for in-depth data querying and analysis to identify inefficiencies and opportunities within the application funnel.

📝 Enhancement Note: This role, while titled "Product Strategy Analyst," has significant overlap with Revenue Operations and Sales Operations responsibilities. The focus on the customer application funnel, conversion optimization, risk assessment, and data-driven decision-making directly impacts revenue generation and operational efficiency. The emphasis on structured experimentation and data analysis aligns with core RevOps/SalesOps principles.

📈 Primary Responsibilities

• Lead analytical and strategic projects to optimize the end-to-end customer application and assessment process for new applicants.

• Identify friction points and inefficiencies within the sign-up funnel through rigorous data analysis, proposing data-backed solutions.

• Design, implement, and evaluate well-structured experiments (e.g., A/B tests) to test alternative customer journeys, product features, and policy changes.

• Develop and recommend improvements to lending strategies, customer assessment methodologies, including document requirements, third-party data utilization, and internal signals.

• Collaborate closely with Engineering, Design, and Data Science teams to scope, prioritize, and implement analytical insights and experimental changes into production systems.

• Present complex analytical findings and strategic recommendations to senior stakeholders, clearly articulating assumptions, uncertainties, and expected commercial impact to drive informed decision-making.

• Monitor the performance of implemented changes, analyzing key metrics to ensure desired outcomes are achieved and iterating as necessary.

• Contribute to the development of credit models and risk assessment frameworks by providing data-driven insights from the application process.

• Work cross-functionally with credit, operations, and product teams to ensure alignment and successful execution of strategic initiatives.

📝 Enhancement Note: The core responsibilities highlight a blend of strategic product thinking and operational execution. The emphasis on "lending strategy" and "assessment process" indicates a direct impact on the company's core revenue-generating activities, aligning this role closely with Revenue Operations principles. The requirement to "turn ideas into shipped changes" implies a hands-on approach to implementation, characteristic of operational roles.

🎓 Skills & Qualifications

Education:

Experience:

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

Required Skills:

• SQL Fluency: Proficient in querying and analyzing large production datasets to extract actionable insights.

• Critical Thinking: Ability to identify underlying assumptions, rigorously examine problems, and propose well-reasoned improvements to product, policy, or process.

• Quantitative Analysis: Strong analytical skills with a solid understanding of statistical principles for data interpretation and experimentation.

• Communication Skills: Ability to clearly articulate statistical results to commercial decision-makers, explain technical concepts to non-technical audiences, and translate findings into actionable strategies.

• Experimentation Design: Understanding of how to design and evaluate structured experiments (e.g., A/B tests) to inform product or policy decisions.

• Commercial Acumen: Ability to connect analytical findings to business objectives and commercial outcomes, such as conversion rates, lending capacity, and portfolio quality.

Preferred Skills:

• Experience designing, running, and interpreting controlled experiments, including A/B tests, to directly inform product or policy decisions.

• Experience working closely with engineering or data science teams to deploy analytical insights into production systems and automate workflows.

• Experience using Python or similar tools for data analysis, prototyping models, or automating analytical workflows.

• Familiarity with credit risk assessment methodologies and their impact on lending strategies.

• Experience with product development lifecycle and cross-functional team collaboration.

📝 Enhancement Note: The emphasis on STEM background, SQL fluency, critical thinking, and structured experimentation are key indicators of the analytical rigor expected in operations roles. The blend of technical skills with commercial judgment and communication is crucial for effective Revenue Operations and Product Strategy roles.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies in Process Optimization: Examples of projects where you identified inefficiencies in a process (e.g., customer application, onboarding, sales funnel) and implemented data-driven improvements.

• Experimentation Design & Results: Demonstrations of well-designed experiments (e.g., A/B tests), including hypotheses, methodologies, and clear articulation of results and their commercial impact.

• Data Analysis & Insights: Portfolios showcasing your ability to query, analyze, and visualize complex datasets to derive actionable business insights, particularly within a customer journey context.

• Strategic Recommendations: Examples of how you translated analytical findings into strategic recommendations that influenced product, policy, or process changes, with measurable outcomes.

Process Documentation:

• Ability to document analytical methodologies, experimental designs, and process improvement proposals clearly and concisely.

• Experience in outlining proposed changes to workflows, assessment criteria, or customer journeys, detailing the potential impact on key performance indicators (KPIs).

• Documentation of how implemented changes were monitored and evaluated against initial objectives.

📝 Enhancement Note: For a role focused on product strategy and application process optimization, a portfolio demonstrating hands-on analytical work, experimental design, and the ability to translate data into strategic, actionable recommendations is critical. This aligns with the expectations for operations professionals who need to prove their impact through quantifiable results and well-documented processes.

💵 Compensation & Benefits

Salary Range: £60,000 - £75,000 per annum.

Benefits:

• Flexible working hours, supporting work-life balance and operational flexibility.

• Comprehensive Medical Insurance from Vitality, including discounted gym membership.

• Private GP service for employees, partners, and dependents, ensuring accessible healthcare.

• Generous holiday entitlement: 25 days per year, plus an extra day for your birthday, with options to buy or sell up to five additional days.

• Unlimited unpaid leave, offering significant flexibility for personal needs.

• A one-month fully paid sabbatical after four years of service, recognizing long-term commitment.

• Instant access to external counselling and therapy sessions for mental health support.

• 3% Pension contributions on total earnings, supporting long-term financial planning.

• Employee equity incentive scheme, providing a stake in the company's success.

• Generous parental leave policies and nursery tax benefit scheme for supporting families.

• Electric car scheme and cycle-to-work scheme, promoting sustainable commuting.

• Two company retreats per year, fostering team cohesion and strategic alignment.

• Dedicated learning and development budget for professional growth.

• Access to company-wide talks with internal and external speakers.

Working Hours:

• Standard full-time hours are implied, but the company offers flexible working hours, allowing for adaptability in scheduling analytical tasks and collaboration.

📝 Enhancement Note: The salary range is provided and is competitive for a mid-level analyst role in London. The benefits package is extensive, with a strong emphasis on employee well-being, professional development, and work-life balance, which are attractive to operations professionals seeking a supportive work environment. The flexible working hours are a significant plus for roles requiring deep analytical focus.

🎯 Team & Company Context

🏢 Company Culture

Industry: FinTech (Lending for Small Businesses)

Company Size: While not explicitly stated, iwoca is described as having a "passionate team" and offices in multiple locations (London, Leeds, Berlin, Frankfurt), suggesting a growing, mid-to-large size company within the FinTech sector. This implies a dynamic environment with opportunities for impact and growth.

Founded: The founding date is not provided, but the company has already facilitated over £4 billion in funding for 100,000 businesses, indicating a mature and established presence in the SME lending market.

Team Structure:

• The New Applications team is central to iwoca's customer acquisition and initial lending process.

• It operates with a degree of autonomy, owning the customer journey from initial interest to loan offer.

• The team comprises individuals with diverse skills, including engineers, designers, data scientists, and credit stakeholders, emphasizing cross-functional collaboration.

Methodology:

• Data-Driven Decision Making: The company strongly emphasizes using data, structured experimentation, and commercial judgment to inform product and policy decisions.

• Customer-Centricity: The mission to support SMEs and improve their access to finance highlights a customer-first approach.

• Agile Development & Iteration: The focus on experimentation and continuous improvement suggests an agile methodology for product development and process optimization.

• Risk Management: Balancing conversion, speed, and accuracy with robust risk assessment is a core operational and strategic methodology.

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

📝 Enhancement Note: Understanding iwoca's focus on SME finance and its mission to support businesses provides crucial context for the Product Strategy Analyst role. The emphasis on data science, technology, and speed suggests an operations environment that values efficiency, innovation, and measurable outcomes. The multi-location presence indicates a potentially global or at least pan-European operational footprint.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a mid-level analyst, suitable for individuals with 2-5 years of experience. It offers a significant opportunity to take ownership of end-to-end projects and directly influence commercial outcomes. It serves as a strong foundation for further specialization in product strategy, data science, or operational leadership within the FinTech sector.

Reporting Structure:

• The Product Strategy Analyst will work closely with engineers, designers, data scientists, and credit stakeholders.

• They will likely report to a Product Manager, Head of Product, or a Senior Analytics/Strategy Lead within the New Applications team.

Operations Impact:

• The role has a direct and significant impact on iwoca's revenue generation by optimizing conversion rates within the application funnel.

• It influences the long-term quality and profitability of the lending portfolio through improved risk assessment and customer selection.

Growth Opportunities:

• Deepening Analytical & Strategic Expertise: Continued development in data analysis, experimentation, and strategic thinking within the FinTech lending space.

• Product Management Track: Potential to transition into a Product Manager role, taking on broader product ownership and roadmap responsibilities.

• Data Science Specialization: Opportunity to further develop advanced data science skills, particularly in areas like predictive modeling and machine learning for credit risk.

• Operational Leadership: Potential to move into leadership roles within operations or analytics teams, managing projects and people.

• Cross-functional Exposure: Gaining broad experience across engineering, design, credit, and marketing functions within a fast-paced FinTech environment.

📝 Enhancement Note: This role offers a clear path for growth within product strategy and operations, with opportunities to specialize or move into leadership. The direct impact on revenue and portfolio quality makes it a high-visibility position, attractive for ambitious operations professionals.

🌐 Work Environment

Office Type: Hybrid work model, with a significant presence in London. This suggests a modern office environment designed for collaboration and focused work, with the flexibility for remote work.

Office Location(s): London, United Kingdom. This central location offers access to a vibrant tech and finance ecosystem.

Workspace Context:

• Collaborative Atmosphere: The emphasis on cross-functional collaboration with Engineering, Design, and Data Science teams indicates a dynamic and interactive workspace.

• Data-Rich Environment: Access to extensive data and analytical tools is implied, supporting data-driven decision-making.

• Innovation Focus: The company culture encourages exploring new areas and improving products, fostering an innovative environment for operations professionals.

• Technology Stack: Expectation of modern technology and tools to support analytical work, experimentation, and product development.

Work Schedule:

• While the role is Full-Time, the company offers flexible working hours, allowing analysts to structure their days to maximize productivity and accommodate personal needs, which is beneficial for deep analytical work and experimentation cycles.

📝 Enhancement Note: The hybrid model and flexible hours in London are key elements of the work environment. For operations roles, this balance of in-office collaboration and remote focus can be highly conducive to complex analytical tasks and strategic planning.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a call with a recruiter to assess basic qualifications, experience, and cultural fit.

• Technical Assessment: This will likely involve a SQL challenge or a data analysis task to evaluate practical skills. Proficiency in SQL is essential.

• Case Study/Project Presentation: Candidates may be asked to prepare and present a case study demonstrating their analytical, strategic thinking, and problem-solving abilities, focusing on a relevant business problem (e.g., conversion optimization, process improvement).

• Cross-functional Interviews: Interviews with team members from Engineering, Data Science, Design, and Credit to assess collaboration skills, technical understanding, and ability to work in a cross-functional setting.

• Hiring Manager Interview: A final discussion with the hiring manager to delve deeper into experience, career aspirations, and alignment with the team's goals and company culture.

Portfolio Review Tips:

• Quantify Impact: For each project in your portfolio, clearly articulate the problem, your approach, the metrics used, and the measurable business impact (e.g., % increase in conversion, % reduction in processing time, $ value of improved risk assessment).

• Showcase Process Thinking: Detail the steps you took in your analysis and problem-solving process, highlighting your critical thinking and structured approach.

• Highlight Experimentation: If you have experience with A/B testing or other experimental designs, provide specific examples of hypotheses, methodologies, and how you interpreted results to drive decisions.

• Tailor to Role: Emphasize projects related to customer journeys, conversion funnels, risk assessment, or process optimization within a financial services or tech context.

• Clarity and Conciseness: Ensure your portfolio is well-organized, easy to understand, and clearly communicates your contributions and achievements.

Challenge Preparation:

• SQL Proficiency: Practice complex SQL queries and be ready to explain your thought process for data extraction and manipulation.

• Experimentation Principles: Review concepts of A/B testing, statistical significance, hypothesis formulation, and common pitfalls.

• Business Case Scenarios: Prepare to analyze a hypothetical business problem related to customer acquisition, conversion, or risk, and propose data-driven solutions.

• Communication Practice: Rehearse explaining technical concepts and analytical results to both technical and non-technical audiences. Be prepared to discuss trade-offs and uncertainties.

📝 Enhancement Note: The interview process will heavily focus on analytical skills (SQL, experimentation) and strategic thinking. A well-prepared portfolio that demonstrates tangible impact and a structured approach to problem-solving will be crucial for success.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Essential for data querying and analysis. Candidates must be fluent.

• Spreadsheet Software: (e.g., Excel, Google Sheets) for data manipulation, basic analysis, and reporting.

• Presentation Software: (e.g., Google Slides, PowerPoint) for communicating findings and recommendations to stakeholders.

Analytics & Reporting:

• Data Warehousing/Analysis Platforms: Likely tools for accessing and analyzing large datasets (specifics not mentioned, but common in FinTech).

• BI Tools: (e.g., Tableau, Looker, Power BI - potential candidates should be familiar with at least one) for data visualization and dashboard creation.

• Statistical Analysis Tools: (e.g., R, Python with libraries like Pandas, NumPy, SciPy) for deeper statistical analysis and modeling.

CRM & Automation:

• While not explicitly a CRM role, understanding customer data flow is key. Familiarity with CRM concepts and how data integrates from various touchpoints is beneficial.

• Experimentation Platforms: (e.g., Optimizely, VWO, or internal tools) for managing A/B tests and other experiments.

• Product Analytics Tools: (e.g., Mixpanel, Amplitude - potential candidates should be familiar with the concepts) for tracking user behavior within the application.

📝 Enhancement Note: Proficiency in SQL is non-negotiable. Experience with Python for data analysis and familiarity with BI/visualization tools and experimentation platforms are highly desirable and align with the operational demands of this role.

👥 Team Culture & Values

Operations Values:

• Data-Driven: A strong commitment to using data and evidence to inform all decisions, from strategy to execution.

• Customer Focus: A dedication to understanding and improving the experience of small business owners seeking finance.

• Continuous Improvement: A mindset of always seeking ways to optimize processes, enhance efficiency, and drive better outcomes.

• Collaboration: A belief in the power of cross-functional teamwork to solve complex problems and achieve shared goals.

• Impact & Ownership: A drive to take ownership of projects and deliver measurable commercial impact.

Collaboration Style:

• Cross-Functional Partnership: Expect active collaboration with diverse teams (Engineering, Design, Data Science, Credit) where open communication and mutual respect are paramount.

• Data-Informed Discussions: Debates and decision-making will be grounded in data analysis and experimental results, fostering a culture of evidence-based strategy.

• Proactive Communication: Regular updates and clear articulation of project status, findings, and challenges to stakeholders across different departments.

• Feedback Integration: Openness to receiving and providing constructive feedback to refine strategies and processes.

📝 Enhancement Note: The company culture emphasizes learning, growth, and support. For an operations analyst, this means an environment where analytical rigor is valued, experimentation is encouraged, and collaboration is key to driving impact.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Competing Priorities: Effectively managing trade-offs between customer friction, information richness, speed, accuracy, and automation in the application process.

• Data Complexity: Working with large, complex datasets and ensuring data integrity for accurate analysis and experimentation.

• Driving Adoption of Insights: Translating analytical findings and experimental results into actionable changes that get adopted by engineering and product teams.

• Navigating Uncertainty: Making informed decisions and recommendations in situations with incomplete data or inherent business uncertainties, particularly in credit risk.

• Keeping Pace with FinTech Innovation: Continuously learning and adapting to new technologies, methodologies, and market dynamics in the rapidly evolving FinTech lending landscape.

Learning & Development Opportunities:

• Advanced Analytics & Experimentation: Deepen expertise in statistical modeling, A/B testing methodologies, and experimental design.

• Product Strategy & Management: Gain exposure to product lifecycle management, roadmap planning, and strategic decision-making.

• FinTech & Credit Risk: Develop specialized knowledge in the unique operational and risk challenges of the SME lending sector.

• Cross-functional Skill Development: Enhance collaboration and communication skills by working with diverse technical and business teams.

• Leadership Potential: Opportunity to take on more complex projects, mentor junior analysts, and potentially move into leadership roles.

📝 Enhancement Note: The challenges presented are typical for roles at the intersection of data, product, and operations in FinTech, offering significant opportunities for skill development and career advancement.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used data to identify a significant opportunity for process improvement or product enhancement. What was your approach, and what was the outcome?"

• "How would you approach designing an experiment to test a new feature in the customer application funnel, considering potential trade-offs between conversion rate, customer experience, and risk?"

• "Given a scenario where a specific customer segment has a high drop-off rate in the application process, how would you investigate the root cause and propose solutions?"

Company & Culture Questions:

• "What interests you about iwoca's mission and its role in supporting SMEs?"

• "How do you approach working with engineers and designers to implement analytical insights?"

• "Describe your experience collaborating with credit or risk teams. How do you ensure analytical insights are aligned with risk appetite?"

Portfolio Presentation Strategy:

• Structure: Clearly define the problem, your methodology (data sources, tools used, analytical techniques), key findings, recommended actions, and the measurable impact achieved.

• Focus on Impact: Quantify results wherever possible. Use metrics that resonate with business objectives (e.g., conversion uplift, revenue impact, efficiency gains).

• Explain Your Role: Be clear about your specific contributions to the project, especially in team-based work.

• Address Challenges: Discuss any challenges encountered and how you overcame them, demonstrating resilience and problem-solving skills.

• Storytelling: Frame your projects as compelling narratives that showcase your analytical prowess and strategic thinking.

📝 Enhancement Note: Interview preparation should focus on demonstrating a blend of technical aptitude (SQL, experimentation), strategic thinking, and strong communication skills, with a clear ability to link data insights to commercial outcomes.

📌 Application Steps

To apply for this Product Strategy Analyst position:

• Submit your application through the provided link on Ashby.

• Tailor Your Resume: Highlight specific experiences related to data analysis, SQL proficiency, structured experimentation, process optimization, and cross-functional collaboration. Use keywords from the job description.

• Prepare Your Portfolio: Curate 2-3 impactful case studies that showcase your analytical skills, experimental design, and ability to drive measurable business outcomes, particularly in customer journey optimization or strategy development.

• Research iwoca: Understand their business model, mission, target market (SMEs), and recent developments. Consider how your skills can contribute to their goals.

• Practice Interview Questions: Prepare to discuss your experience with the strategy, technical, and behavioral questions outlined above, and be ready to present your portfolio effectively.

⚠️ 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.

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