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Valerie Group
Valerie Group
11 – 50 Darbinieki
B2BElektroniskā komercijaMārketings
Valerie Group palīdz tiešās pārdošanas e-komercijas zīmoliem veidot un paplašināt izaugsmes operācijas. Uzņēmums apvieno patentētu mākslīgā intelekta analītikas platformu ar pieredzējušiem speciālistiem maksas mediju, radošā satura, reklāmguvumu līmeņa optimizācijas, e-pasta mārketinga, SEO, tehnoloģiju un stratēģijas jomā. Tā darbs balstās strukturētā eksperimentēšanā, tostarp A/B testēšanā un pilotprogrammās, apvienojot uz rezultātiem vērstu izpildi ar iespējamu uz rezultātiem balstītu kapitālu, kas paredz atlikt līdzdalības samazināšanos līdz brīdim, kad rezultāti ir pierādīti. Valerie Group sadarbojas ar digitāli veidotiem patēriņa zīmoliem, izmantojot integrācijas ar tādām platformām kā Shopify, Meta, Google, TikTok un Amazon, koncentrējoties uz izmērāmu izaugsmi un atkārtojamām darbības sistēmām.
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Vakances uzņēmumā

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.

INIndijaHibrīdiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuDatu zinātnieks
BigQueryNumpyPandasPythonScikit-LearnSQLTableau

Apraksts

  • 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.

Prasības

  • 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.

Priekšrocības

  • 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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