UX Analytics Lead (Python, SQL)

📍 Job Overview

Job Title: UX Analytics Lead (Python, SQL)

Company: Capgemini

Location: Wroclaw, Warszawa, Poznan, Lublin, Gdansk, Kraków, Opole, Katowice, PL

Job Type: Full-Time

Category: Data & Analytics / UX Research Operations

Date Posted: 2026-06-10

Experience Level: 5-10 Years

Remote Status: Hybrid

🚀 Role Summary

• Lead the establishment and scaling of UX analytics across a portfolio of enterprise products, transforming user behavior data into actionable insights.

• Drive product and design improvements by translating complex user behavior into clear, impactful recommendations for cross-functional teams.

• Define, standardize, and champion key UX metrics (e.g., task success, engagement, efficiency) to measure product performance and user experience quality.

• Develop and implement scalable analytics practices, including frameworks, dashboards, and best practices, to ensure consistent and effective data utilization.

• Mentor and guide researchers and designers in leveraging data analytics to enhance user experience and achieve product goals.

📝 Enhancement Note: This role is positioned within a "best-in-class UX organization" at Capgemini, indicating a strategic focus on elevating user experience through data-driven decision-making. The emphasis on "enterprise products" suggests a need for experience in complex, large-scale environments. The "UX Analytics Lead" title implies a leadership position responsible for setting standards and driving adoption of analytics practices within the UX domain.

📈 Primary Responsibilities

• Analyze intricate user behavior patterns across key applications to pinpoint friction points and identify opportunities for experience enhancement.

• Synthesize quantitative data from analytics tools and qualitative insights from research to provide holistic explanations for user actions and product performance.

• Define, implement, and monitor a comprehensive suite of UX metrics, including task success rates, user drop-off points, engagement levels, and interaction efficiency.

• Map and optimize user journeys and conversion funnels for critical applications, ensuring a seamless and effective user flow.

• Establish clear success criteria for new features and product releases, utilizing data to validate hypotheses and measure impact.

• Design, execute, and analyze experimentation initiatives, such as A/B testing and feature validation studies, to inform product development.

• Build and maintain scalable analytics frameworks, including the development of interactive dashboards and the documentation of best practices for data analysis and reporting.

• Provide guidance and mentorship to UX researchers and designers, fostering a data-informed culture and empowering them to utilize analytics effectively in their work.

• Collaborate closely with product managers, engineers, and other stakeholders to ensure analytics insights are integrated into the product development lifecycle.

• Advocate for data-driven design principles and practices throughout the organization, promoting a deeper understanding of user needs and behaviors.

📝 Enhancement Note: The responsibilities highlight a blend of strategic leadership (establishing practices, defining metrics) and hands-on execution (analyzing data, designing experiments). The emphasis on combining quantitative and qualitative insights is crucial for a deep understanding of "what is happening and why." The need to "mentor researchers and designers" indicates a senior-level role with a strong focus on knowledge transfer and team enablement.

🎓 Skills & Qualifications

Education: Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, Psychology, Human-Computer Interaction, or a related discipline. Master's degree or equivalent practical experience is a strong plus.

Experience: Minimum of 5 years of progressive experience in product analytics, quantitative UX research, or a closely related analytical role within technology or consulting environments. Experience in complex or enterprise-level product environments is highly valued.

Required Skills:

• Proven expertise in product analytics and quantitative UX research methodologies.

• Demonstrated ability to translate complex data into clear, actionable recommendations for design and product teams.

• Hands-on experience with leading product analytics platforms such as Amplitude, Mixpanel, Google Analytics, or similar tools.

• Proficient in structuring ambiguous problems, defining meaningful key performance indicators (KPIs), and establishing success criteria.

• Solid understanding and practical experience with experimentation frameworks, including A/B testing design, execution, and analysis.

• Strong data querying skills using Python and/or SQL for data extraction, manipulation, and analysis.

• Experience collaborating closely with UX/design and product management teams to influence product strategy and development.

• Ability to combine quantitative user behavior data with qualitative insights for a comprehensive understanding of user experience. Preferred Skills:

• Experience in designing and implementing scalable analytics practices, including framework development and dashboard creation.

• Familiarity with data visualization tools (e.g., Tableau, Power BI) for creating compelling reports and presentations.

• Experience mentoring or coaching junior analysts, researchers, or designers on data utilization.

• Knowledge of advanced statistical techniques for analyzing user behavior and experimental results.

• Experience within a global consulting firm like Capgemini, understanding diverse client needs and project complexities.

• Familiarity with AI/ML concepts and their application in user behavior analysis.

📝 Enhancement Note: The requirement for 5+ years of experience, coupled with the need for hands-on tool proficiency and advanced analytical skills (Python, SQL), positions this as a senior-level role. The emphasis on "turning data into product or design decisions" and "structuring ambiguous problems" indicates a need for strong analytical rigor and strategic thinking. The preference for experience in "complex or enterprise environments" suggests that candidates with experience in large, established organizations will have an advantage.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies of Impact: Showcase 2-3 detailed case studies demonstrating how your analytics initiatives led to measurable improvements in user experience, product adoption, or business outcomes. Each case study should clearly outline the problem, your analytical approach, the tools and methodologies used, the insights derived, and the tangible results achieved.

• Metric Definition & Tracking: Provide examples of how you defined, implemented, and tracked key UX metrics. This could include visualizations of dashboards you've built or documentation of metric frameworks you've established.

• Experimentation Design: Include examples of A/B tests or other experiments you've designed and analyzed, detailing your hypothesis, methodology, and the conclusions drawn, along with any subsequent product changes.

• Data Storytelling: Demonstrate your ability to translate complex data into compelling narratives that influence stakeholders. This could be through presentation slides from past projects or sample reports.

• System Integration & Collaboration: Briefly describe how you've integrated analytics tools and processes with other systems (e.g., CRM, product management tools) and collaborated with cross-functional teams.

Process Documentation:

• Workflow Design & Optimization: Evidence of designing and optimizing user analytics workflows, from data collection and processing to analysis and reporting. This includes creating standardized processes for user journey mapping and funnel analysis.

• Framework Development: Examples of developing reusable frameworks for UX metric definition, experimentation, and data analysis that can be scaled across multiple products or teams.

• Measurement & Performance Analysis: Documentation of how you establish success criteria for features and product releases and how you measure and report on performance against these criteria.

📝 Enhancement Note: For a "Lead" role, a portfolio is crucial. It should not only showcase technical skills but also the ability to drive strategic impact and influence product decisions. Demonstrating the development of scalable practices and frameworks, rather than just individual analyses, will be key. The emphasis on "enterprise environments" means showcasing experience with complex data structures and stakeholder management is important.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for a UX Analytics Lead with 5-10 years of experience in Poland, a competitive salary range is estimated to be between 18,000 PLN and 28,000 PLN gross per month. This range can vary based on specific experience, negotiation, and the exact location within Poland.

Benefits:

• Comprehensive Well-being Program: Medical care with Medicover, private life insurance, and a Sports card.

• Mental Health Support: Access to therapeutic support via the Capgemini Helpline and educational content through the "Let's talk about wellbeing" podcast.

• Extensive Learning & Development: Over 70 training tracks on the NEXT platform with certification opportunities (e.g., GenAI, Excel, Business Analysis, Project Management), free access to Education First languages platform, TED Talks, and Udemy Business materials.

• Performance Management: Continuous feedback and ongoing performance discussions facilitated by the GetSuccess tool and a transparent policy.

• Hybrid Working Model: Flexible work arrangement combining office and remote work, with a home office package (laptop, monitor, chair) provided after onboarding.

• Professional Development: Opportunities for continuous learning, skill development, and potential career advancement within Capgemini's global network.

Working Hours: Standard full-time working hours are expected, likely around 40 hours per week, with flexibility offered through the hybrid working model. Specific core hours will be determined by team needs and project requirements.

📝 Enhancement Note: Salary estimation is based on research for similar roles in Poland, considering the experience level (5-10 years), the specific skill set (Python, SQL, UX Analytics tools), and the company's standing as a large global consulting firm. The benefits package is extensive and clearly detailed in the job description, highlighting Capgemini's investment in employee well-being and professional growth.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, IT Services, Consulting, Digital Transformation, AI. Capgemini operates globally, advising and transforming organizations across various sectors.

Company Size: Over 420,000 employees worldwide, making it a very large enterprise with extensive resources and opportunities.

Founded: Nearly 60 years ago, indicating a long-standing history and established presence in the market.

Team Structure:

• The role is part of a "best-in-class UX organization" being built, suggesting a dedicated and growing team focused on user experience.

• The UX Analytics Lead will likely work within a product line or a dedicated UX/design department, collaborating closely with product managers, UX researchers, UI designers, and engineering teams.

• Reporting structure is not explicitly detailed but is expected to be within a product or digital transformation unit, with potential for leadership within the analytics function. Methodology:

• Data-Driven Decision Making: A core tenet, emphasizing the use of data (quantitative and qualitative) to inform strategy, design, and product development.

• Agile & Iterative Development: Common in technology and consulting, likely involving iterative processes for analytics framework development and experimentation.

• Cross-Functional Collaboration: Essential for integrating UX insights across different departments and ensuring alignment on product goals.

• Focus on Business Value: Capgemini's mission is to "deliver tangible business value," so all analytics efforts will be geared towards achieving measurable business outcomes.

Company Website: https://www.capgemini.com/

📝 Enhancement Note: Capgemini's scale means this role operates within a large, complex organization. The opportunity to "establish and scale analytics" suggests a greenfield or early-stage initiative within UX, offering significant influence. The company's commitment to AI-powered transformation and sustainability provides context for the types of projects and challenges the UX Analytics Lead might encounter.

📈 Career & Growth Analysis

Operations Career Level: This is a "Lead" position, signifying a senior individual contributor role with leadership responsibilities in a specialized domain (UX Analytics). It sits above junior analyst or researcher roles and below management positions overseeing entire departments. The role requires strategic thinking, technical expertise, and the ability to influence without direct authority.

Reporting Structure: While not explicitly stated, the Lead would likely report to a Head of UX, Director of Product Analytics, or a senior Product Management leader. They would be expected to work autonomously, defining their own priorities within the broader UX and product strategy.

Operations Impact: The UX Analytics Lead has a direct impact on the success of enterprise products by ensuring they meet user needs and achieve business objectives. By turning user behavior into actionable insights, they influence product design, feature prioritization, and overall user experience strategy, which in turn drives customer satisfaction, retention, and revenue growth.

Growth Opportunities:

• Technical Specialization: Deepen expertise in advanced analytics techniques, experimentation design, and emerging UX analytics tools and AI applications.

• Leadership Development: Transition into management roles, leading a team of UX analysts or researchers, or taking on broader product analytics responsibilities.

• Strategic Influence: Become a key advisor on UX strategy and data-driven product development across multiple product lines or business units.

• Cross-Functional Mobility: Potentially move into product management, UX research management, or even business consulting roles leveraging their analytical and strategic skills.

• Global Opportunities: Leverage Capgemini's international presence for diverse project experiences and potential international assignments.

📝 Enhancement Note: The "Lead" title implies significant autonomy and the expectation to set direction. Growth opportunities are likely tied to expanding the scope of analytics impact, developing a team, and influencing strategic product decisions at a higher level. Capgemini's large size offers a broad canvas for career progression.

🌐 Work Environment

Office Type: Hybrid working model, balancing remote work with in-office collaboration. Capgemini likely offers modern office spaces designed for collaboration.

Office Location(s): Multiple locations across Poland, including Wroclaw, Warszawa, Poznan, Lublin, Gdansk, Kraków, Opole, and Katowice. This provides flexibility for candidates within these regions.

Workspace Context:

• Collaborative Environment: The hybrid model and emphasis on cross-functional work suggest a collaborative office setting, with spaces designed for team meetings, brainstorming sessions, and focused work.

• Technology & Tools: Access to necessary technology, including a provided home office package (laptop, monitor, chair), and the latest analytics software and tools required for the role.

• Team Interaction: Opportunities to connect with UX researchers, designers, product managers, and other analytics professionals, fostering knowledge sharing and professional development.

Work Schedule: The role is full-time with a hybrid arrangement, allowing for flexibility in managing work-life balance. Specific core hours and days in the office will likely be team-dependent and discussed during the hiring process.

📝 Enhancement Note: The hybrid model is a significant aspect of the work environment, offering flexibility. Candidates should be comfortable with a mix of remote and in-office work, and the specific office locations provided offer accessibility to a wide talent pool across Poland. The "modern office" description suggests a professional and well-equipped workspace.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or Recruiter call to assess basic qualifications, cultural fit, and salary expectations.

• Technical Interview(s): In-depth discussions focusing on your experience with Python, SQL, product analytics tools (Amplitude, Mixpanel), experimentation, and UX metrics. This may involve live coding exercises or problem-solving scenarios.

• Portfolio Presentation: A dedicated session where you present your case studies and demonstrate your ability to translate data into actionable insights and drive product decisions. Be prepared to discuss your process, challenges, and impact.

• Hiring Manager/Team Interview: Discussion with the hiring manager and potential team members to assess leadership potential, collaboration skills, strategic thinking, and alignment with Capgemini's culture.

• Final Round: May involve a case study or a strategic discussion with senior leadership.

Portfolio Review Tips:

• Quantify Impact: For each case study, clearly state the metrics improved and the percentage or absolute change achieved.

• Showcase Process: Detail your analytical process from problem definition to insight delivery and impact measurement.

• Highlight Collaboration: Emphasize how you worked with designers, product managers, and engineers to implement recommendations.

• Tailor to Capgemini: Research Capgemini's services, clients, and recent initiatives to frame your experience in a relevant context.

• Be Concise but Thorough: Present the most impactful projects clearly and be ready to dive deeper into any aspect upon request.

Challenge Preparation:

• Problem-Solving: Practice approaching ambiguous problems, defining relevant metrics, and outlining analytical steps.

• Technical Skills: Brush up on Python (libraries like Pandas, NumPy) and SQL for data manipulation and analysis. Review common UX analytics concepts and tools.

• Experimentation: Understand the principles of A/B testing, sample size calculation, statistical significance, and common pitfalls.

• Data Storytelling: Prepare to explain complex findings simply and persuasively, focusing on the "so what?" for business stakeholders.

📝 Enhancement Note: The portfolio presentation is a critical component for this role. Candidates should prepare to explicitly demonstrate their impact through concrete examples and be ready to articulate their thought process and methodology in detail. The interview process is likely multi-stage, with a strong emphasis on both technical proficiency and strategic influence.

🛠 Tools & Technology Stack

Primary Tools:

• Product Analytics Platforms: Hands-on experience with Amplitude, Mixpanel, Google Analytics, or similar platforms for tracking user behavior, engagement, and conversions.

• Data Querying & Manipulation: Proficiency in Python (with libraries like Pandas, NumPy, SciPy) and SQL for complex data extraction, transformation, and analysis.

• Experimentation Platforms: Experience designing and analyzing A/B tests and other experiments using tools like Optimizely, VWO, or built-in platform capabilities.

Analytics & Reporting:

• Data Visualization Tools: Familiarity with tools such as Tableau, Power BI, Looker, or similar for creating dashboards and reports to communicate insights effectively.

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

CRM & Automation:

• CRM Systems: Understanding of how CRM data (e.g., Salesforce) can be integrated with product analytics for a more holistic view of the customer journey.

• Data Warehousing/Lakes: Experience working with data stored in data warehouses or data lakes may be beneficial.

📝 Enhancement Note: The core technical requirements revolve around product analytics platforms and data manipulation tools (Python/SQL). Experience with experimentation platforms and data visualization tools is also highly valued for communicating insights. The role requires a strong analytical toolkit to effectively "establish and scale analytics."

👥 Team Culture & Values

Operations Values:

• Data-Driven: A strong emphasis on using data to inform decisions, measure impact, and drive continuous improvement in user experience and product performance.

• Collaboration: A culture of working effectively with cross-functional teams (UX, Product, Engineering) to achieve shared goals and integrate insights seamlessly.

• Innovation: Encouraging new approaches to analytics, experimentation, and problem-solving to push the boundaries of user experience.

• Customer-Centricity: A deep commitment to understanding and serving user needs, ensuring that product development is guided by user behavior and feedback.

• Excellence: Striving for high quality in analysis, reporting, and strategic recommendations, aiming for tangible business value.

Collaboration Style:

• Partnership-Oriented: Working closely with product managers and designers as strategic partners, not just as a service provider.

• Proactive Communication: Regularly sharing insights, findings, and recommendations to keep stakeholders informed and engaged.

• Constructive Feedback: Open to receiving and providing feedback to foster continuous improvement within the team and across projects.

• Knowledge Sharing: Actively participating in sharing best practices, learnings, and new analytical techniques with colleagues.

📝 Enhancement Note: Capgemini's global nature and focus on transformation suggest a culture that values innovation, diversity, and a results-oriented approach. For this role, a collaborative, data-driven, and customer-centric mindset will be essential for success, especially in building out the UX analytics function.

⚡ Challenges & Growth Opportunities

Challenges:

• Establishing Analytics Frameworks: As this is a role to "establish and scale analytics," a primary challenge will be building the foundational processes, metrics, and tools from the ground up or significantly enhancing existing ones.

• Data Complexity & Ambiguity: Working with enterprise products can mean dealing with large, complex datasets and ambiguous user behavior, requiring strong problem-solving skills to extract meaningful insights.

• Influencing Stakeholders: Convincing diverse teams (designers, product managers, engineers) to adopt data-driven recommendations and prioritize analytics-informed changes.

• Measuring ROI of UX: Quantifying the direct business impact of UX improvements can be challenging, requiring sophisticated analytical approaches and strong storytelling.

• Keeping Pace with Technology: The rapid evolution of analytics tools, AI, and user behavior tracking methods requires continuous learning and adaptation.

Learning & Development Opportunities:

• Advanced Analytics & AI: Access to training on cutting-edge analytics techniques, machine learning applications in UX, and Generative AI for insights generation.

• Experimentation Mastery: Deepen expertise in experimental design, statistical modeling, and causal inference for more robust product validation.

• Leadership & Mentorship: Opportunities to develop leadership skills by mentoring junior team members and potentially leading analytics initiatives.

• Industry Exposure: Working with a diverse range of clients and projects within Capgemini can provide broad industry knowledge and exposure to various business challenges.

• Certifications: Pursue certifications in analytics, UX, or project management through Capgemini's extensive learning platforms.

📝 Enhancement Note: The challenges are directly linked to the opportunity to build and scale. Candidates should be prepared for a dynamic environment where they will define processes. The growth opportunities are substantial, leveraging Capgemini's resources for continuous professional development.

💡 Interview Preparation

Strategy Questions:

• "How would you approach establishing a UX analytics framework for a new enterprise product line at Capgemini, considering our diverse client base?" (Focus on your methodology, scalability, and stakeholder engagement).

• "Describe a time you used both quantitative and qualitative data to explain a complex user behavior issue and what product changes resulted." (Highlight your analytical process, insight synthesis, and impact).

• "How do you define and measure success for UX initiatives? Can you share an example of how you set product success criteria and tracked performance?" (Demonstrate your understanding of metrics, KPIs, and outcome-based analysis). Company & Culture Questions:

• "What do you know about Capgemini's approach to digital transformation and AI, and how do you see UX analytics playing a role in that?" (Show research into Capgemini's strategic pillars).

• "How do you foster a data-driven culture within teams that may not be as analytically inclined?" (Discuss your communication, mentorship, and influencing strategies).

• "When faced with conflicting data or stakeholder opinions, how do you reach a consensus and make data-driven recommendations?" (Assess your problem-solving, negotiation, and communication skills). Portfolio Presentation Strategy:

• Structure: For each case study, use a clear STAR (Situation, Task, Action, Result) or similar framework. Clearly articulate the business problem, your role, the specific actions you took (analysis, experimentation), and the measurable results.

• Visuals: Use clear, concise charts and graphs to illustrate data and findings. Avoid overwhelming slides with too much text.

• Focus on Impact: Emphasize the business value and product improvements driven by your work, quantifying outcomes whenever possible.

• Technical Depth: Be prepared to discuss the specific tools, techniques, and statistical methods you employed.

• Q&A Readiness: Anticipate questions about your methodology, challenges faced, and alternative approaches you considered.

📝 Enhancement Note: Interview questions will likely probe your ability to apply analytical skills to complex business problems within a consulting context. Preparing specific examples from your past experience, tailored to Capgemini's focus on digital transformation and AI, will be key. The portfolio presentation is your chance to shine, so ensure it's well-rehearsed and impactful.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided careers link: https://careers.capgemini.com/job/Katowice-UX-Analytics-Lead-%28Python%2C-SQL%29/1402859733/

• Tailor Your Resume: Highlight your experience with Python, SQL, product analytics tools (Amplitude, Mixpanel), A/B testing, and driving product decisions through data. Quantify your achievements with specific metrics and impact.

• Prepare Your Portfolio: Curate 2-3 of your most impactful UX analytics case studies. Focus on demonstrating your ability to define metrics, analyze behavior, conduct experiments, and translate findings into actionable recommendations that led to measurable product improvements.

• Research Capgemini: Understand Capgemini's services, particularly in digital transformation, AI, and consulting. Familiarize yourself with their commitment to client success and innovation.

• Practice Your Presentation: Rehearse presenting your portfolio case studies, focusing on clear communication, data storytelling, and articulating the business value of your work. Be ready for technical questions about your methodologies and tools.

⚠️ 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.