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Valerie Group
Valerie Group
11 – 50 Darbuotojai
B2BElektroninė prekybaRinkodara
„Valerie Group“ padeda tiesiogiai vartotojams parduodantiems elektroninės prekybos prekių ženklams kurti ir plėsti augimo operacijas. Įmonė derina nuosavą dirbtiniu intelektu pagrįstą analitikos platformą su patyrusiais specialistais mokamos reklamos, kūrybos, konversijų rodiklio optimizavimo, el. pašto rinkodaros, SEO, technologijų ir strategijos srityse. Jos darbas grindžiamas struktūruotu eksperimentavimu, įskaitant A/B testavimą ir bandomąsias programas, o į rezultatus orientuotas įgyvendinimas derinamas su galimu rezultatais grindžiamu kapitalu, skirtu atidėti dalies nuosavybės praskiedimą, kol bus įrodyti rezultatai. „Valerie Group“ dirba su skaitmeniniu būdu sukurtais vartotojų prekių ženklais, integruodama tokias platformas kaip „Shopify“, „Meta“, „Google“, „TikTok“ ir „Amazon“, daugiausia dėmesio skirdama išmatuojamam augimui ir pakartojamoms veiklos sistemoms.
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Darbai įmonėje

Data Scientist, Product Analytics & AI — Valerie Group (Hybrid, India)

Lead product analytics, modeling, experimentation, and AI initiatives across Valerie Group’s brands and investment growth platform. Turn SQL and Python analysis into production-ready commercial and product solutions.

INIndijaHibridinisVisas etatasVidutinis lygisVyresnysis specialistasPrivaloma Kalba: anglųDuomenų mokslininkas
BigQueryNumpyPandasPythonScikit-LearnSQLTableau

Aprašymas

  • Lead growth, commercial, and product analytics alongside applied data science and AI initiatives across Valerie Group’s brands and investment growth platform.
  • Establish and monitor product metrics, user behavior, funnels, drop-offs, and feature performance.
  • Turn product questions into structured analyses and practical recommendations.
  • Develop and apply models for segmentation, scoring, classification, recommendations, forecasting, unit economics, incrementality, media effectiveness, and other decision-making needs.
  • Work with Engineering and Data teams to operationalize models and analytical workflows.
  • Use incomplete, imperfect, or banded data while documenting assumptions and identifying significant data gaps.
  • Manage analytical and modeling projects from defining the business problem and data requirements through modeling, validation, deployment, and impact measurement.
  • Design and conduct A/B tests and cohort analyses.
  • Assess the effects of product changes, AI outputs, and workflow adjustments.
  • Create feedback loops that improve product and model performance.
  • Quantify uncertainty, challenge assumptions, and communicate limitations and confidence levels.
  • Specify data requirements for product features and support accurate, consistent, and complete tracking.
  • Partner with Engineering to organize datasets and data pipelines.
  • Find and address gaps in data visibility.

Reikalavimai

  • Six to eight years of relevant analytics or data science experience.
  • Ability to turn ambiguous business, product, growth, or commercial challenges into structured data questions and actionable analytical plans.
  • Experience analyzing product metrics, funnels, and user behavior.
  • Experience developing and applying classification, regression, clustering, scoring, forecasting, and decision models.
  • Demonstrated experience bringing at least one meaningful model or analytical product into business use.
  • Strong understanding of CAC, AOV, COGS, contribution margin, payback period, and breakeven.
  • Advanced SQL skills.
  • Experience working with structured and semi-structured data.
  • Strong working proficiency in Python for data analysis, modeling, experimentation, and automation; equivalent analytics capability in R is also acceptable.
  • Proficiency with pandas, NumPy, and scikit-learn.
  • Experience with A/B testing, statistical analysis, measurement, causality, and impact evaluation.
  • Experience assessing LLM- or AI-generated outputs in product workflows.
  • Experience with Tableau, Power BI, or Metabase is preferred but not required.
  • Experience in a zero-to-one startup environment is preferred but not required.
  • Experience with media mix modeling, incrementality, causal inference, experimental design, or media effectiveness measurement is preferred but not required.
  • Experience with Snowflake, BigQuery, dbt, Triple Whale, Northbeam, or Rockerbox is preferred but not required.
  • Experience deploying machine learning models to production is preferred but not required.

Privalumai

  • Competitive compensation package.
  • Access to the tools required to perform effectively.
  • Growth opportunities as Valerie Group expands.
  • Work with meaningful, measurable impact.
  • Significant ownership from the start.
  • Collaboration with experienced founders, operators, and specialists.
  • Inclusive working environment.
  • A role-specific assessment or practical exercise when applicable.

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