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Valerie Group
Valerie Group
11 – 50 Employees
B2BeCommerceMarketing
Valerie Group helps direct-to-consumer e-commerce brands build and scale growth operations. The company combines a proprietary AI intelligence platform with experienced human operators across paid media, creative, conversion rate optimization, email, SEO, technology, and strategy. Its work is grounded in structured experimentation, including A/B testing and pilot programs, and it connects performance-focused execution with potential performance-based capital designed to defer dilution until results are demonstrated. Valerie Group works with digital-native consumer brands through integrations with platforms such as Shopify, Meta, Google, TikTok, and Amazon, with a focus on measurable growth and repeatable operating systems.
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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.

INIndiaHybridFull-timeMiddleSeniorEnglish RequiredData Scientist
BigQueryNumpyPandasPythonScikit-LearnSQLTableau

Description

  • 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.

Requirements

  • 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.

Benefits

  • 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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