Valerie Group тұтынушыға тікелей сататын электрондық коммерция брендтеріне өсу операцияларын құруға және ауқымын кеңейтуге көмектеседі. Компания ақылы медиа, креатив, конверсия деңгейін оңтайландыру, электрондық пошта, SEO, технология және стратегия бағыттарындағы тәжірибелі мамандарды жеке AI-талдау платформасымен біріктіреді. Оның жұмысы A/B тестілеу мен пилоттық бағдарламаларды қоса алғанда, құрылымдалған эксперименттерге негізделген. Сонымен қатар компания нәтижелер дәлелденгенге дейін үлестің сұйылуын кейінге қалдыруға арналған ықтимал нәтижеге негізделген капиталды өнімділікке бағытталған іске асырумен ұштастырады. Valerie Group Shopify, Meta, Google, TikTok және Amazon сияқты платформалармен интеграциялар арқылы цифрлық ортада қалыптасқан тұтынушылық брендтермен жұмыс істейді және өлшенетін өсімге, қайталанатын операциялық жүйелерге назар аударады.
Senior Data Analytics Expert
Build growth forecasts and brand profit-and-loss systems for Valerie Group. Turn quantitative models and AI workflows into practical tools for commercial decisions.
Сипаттама
- Develop and maintain a rigorous 12-month growth forecasting methodology
- Build brand-level profit-and-loss statements from forecasts, mapping revenue, cost of goods sold, contribution margin, and operating costs
- Compare model forecasts with actual results, measure errors, track variances, and explain differences
- Turn financial and statistical models into production-ready product logic
- Define AI agent calculations, data sources, benchmarks, and claims the agents must not make
- Set up human review checkpoints before deliverables are released
- Work with engineering to define data schemas, validation rules, and pipelines
- Create analyses focused on specific commercial decisions
- Measure uncertainty and assign confidence levels to outputs
- Create and maintain versioned benchmarks by category, stage, and market
- Explain complex models and uncertainty to founders and operators
- Help teams interpret model outputs accurately
- Document data and finance standards so teams can work independently across functions
Талаптар
- 6–8 years of experience in growth, marketing, commercial, or product analytics in direct-to-consumer, e-commerce, marketplaces, or specialized platforms
- End-to-end ownership of a forecasting, unit economics, or media mix model used by commercial teams for high-stakes budget or strategy decisions
- Strong command of customer acquisition cost, average order value, cost of goods sold, contribution margin, lifetime value, payback period, breakeven, retention cohorts, and working capital reconciliation
- Ability to produce robust analyses from approximate ranges, self-reported figures, or incomplete founder inputs, while clearly quantifying confidence
- Strong grounding in uncertainty estimation, sample limitations, and analytical integrity
- Daily hands-on proficiency with SQL and Python
- Experience partnering directly with engineering to turn quantitative models or metric definitions into production software
- Strong communication skills and the ability to defend assumptions and explain model uncertainty under challenge
- Media mix modeling, incrementality testing, or causal measurement experience is a plus
- Experience deploying machine learning in production is a plus
- Experience evaluating generative AI or multi-agent system outputs is a plus
- Familiarity with Snowflake, BigQuery, dbt, Triple Whale, Northbeam, or Rockerbox is a plus
- Experience with multi-brand businesses through agency, consulting, or platform work is a plus
- Experience co-developing models and products from scratch in an early-stage product environment is a plus
Артықшылықтар
- Meaningful work with visible impact
- Significant ownership from the first day
- Work alongside experienced founders, operators, and specialists
- A team that values curiosity, initiative, and continual improvement
- Competitive compensation and the tools needed to do your best work
- Room to grow as Valerie grows
- An inclusive workplace where people with different backgrounds, experiences, and perspectives can thrive