{"id":1712520,"url":"https://alion.io/job/moonpig-product-analytics-experimentation-lead","title":"Lead Product Analyst","company":{"id":51474,"name":"Moonpig","domain":"moonpig.com","url":"https://alion.io/company/moonpig","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":86000,"max_usd":160000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":19},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"SQL","optional":false},{"name":"Python","optional":true},{"name":"Snowflake","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-10-02T16:04:52Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-15T00:38:03Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Lead Product Analyst | London - Hybrid (1-2 days per week) | Competitive Salary + Benefits\nAbout the Role\nAre you passionate about turning customer behaviour into better digital experiences? As our Lead Product Analyst, you'll help shape how millions of customers interact with Moonpig by uncovering insights that drive smarter product decisions.\nThis is a senior individual contributor role where you'll partner closely with Product, Data and Engineering teams to understand customer behaviour, identify opportunities to improve the customer journey, and help teams measure the impact of the changes they make.\nYou'll play a key role in building confidence in our product metrics, improving experimentation practices, and enabling teams to make evidence-based decisions. If you enjoy solving complex problems, translating data into clear recommendations and helping others learn from customer behaviour, we'd love to hear from you.\nKey Responsibilities:\nPartner with Product teams to understand customer journeys, product questions and opportunities to improve the customer experience.\nConduct exploratory behavioural analysis using techniques including funnel, journey, cohort, segmentation and retention analysis.\nTranslate analytical findings into clear, practical recommendations that help teams prioritise what to improve next.\nDefine, maintain and govern product and behavioural metrics to ensure consistent, reliable measurement across teams.\nValidate product tracking and data quality, working closely with Data and Engineering colleagues to resolve issues.\nProvide guidance on experimentation best practice, including hypotheses, success metrics, test validity and interpretation of results.\nDevelop repeatable frameworks, documentation and resources that enable consistent measurement and learning across Product teams.\nBuild confidence across teams in using behavioural data to inform product decisions.\nCollaborate with cross-functional partners to champion strong analytical thinking and customer-focused decision making.\nAbout You:\nSignificant experience in Product Analytics, Customer Analytics or a similar role within a digital product or e-commerce environment.\nStrong hands-on SQL skills with the ability to investigate data, challenge assumptions and communicate findings clearly.\nExperience exploring customer behaviour through funnel, journey, cohort, segmentation or retention analysis.\nProven ability to define, maintain and govern product metrics to improve the quality and consistency of measurement.\nExperience supporting experimentation through structured testing, robust measurement and thoughtful interpretation of results.\nExcellent communication skills with the ability to explain complex analysis in a clear and practical way.\nStrong collaboration skills and experience partnering with Product and cross-functional teams.\nExperience creating analytical frameworks, documentation or resources that help teams measure products consistently.\nComfortable working through ambiguity while remaining focused on customer behaviour and product outcomes.\nNice to Have:\nWorking knowledge of Python.\nExperience with product analytics platforms such as Mixpanel, Amplitude or similar.\nFamiliarity with Snowflake, Tableau or comparable data platforms.\nExperience using causal inference techniques such as regression, matching, difference-in-differences or uplift modelling.\nExperience evaluating recommendation, personalisation or AI-enabled product features.\nExperience sharing analytical knowledge through coaching, documentation or communities of 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