Data Scientist With Python Expertise In New York

Capgemini

New York, NY, US
Base: $100,000 to $130,000; bonus/equity: not spec...
On-site
Multi-touch attribution (mta) models
Ltv/cac scoring models
Holdout and matched-market test frameworks
Build and maintain multi-touch attribution (MTA) models with incremental lift quantification across various channels

Job Summary

  • Build and maintain multi-touch attribution (MTA) models with incremental lift quantification across various channels.
  • Develop cohort-level LTV/CAC scoring models and design test frameworks for measuring incrementality.
  • Collaborate with engineering to design system prompts and evaluation frameworks for AI-powered audience authoring and measurement intelligence.

Matching Summary

Build and maintain multi-touch attribution (MTA) models with incremental lift quantification across various channels.

Salary

Base: $100000 to $130000; Bonus/Equity: Not specified; Benefits: Comprehensive, non-negotiable benefits package

Skills & Requirements

Must-have

  • multi-touch attribution (MTA) models
  • LTV/CAC scoring models
  • holdout and matched-market test frameworks
  • probabilistic identity linkage models
  • SHAP-based feature importance pipelines
  • behavioral micro-cohort clustering
  • AI-powered audience authoring
  • geo-level DMA performance models
  • AI-assisted insight narratives

Nice-to-have

  • AI-augmented analytics workflows
  • walled garden measurement environments
  • graph-based modeling experience
  • identity resolution at scale

Key Requirements

  • 5+ years applied data science experience
  • Expert Python proficiency
  • Deep expertise in multi-touch attribution methodologies
  • Experience building LTV, propensity, and CAC models
  • Comfort operating inside data clean rooms
  • Strong statistical foundations
  • Fluent SQL across cloud data warehouses
  • Experience working with ML platforms

Work Rights

Not specified

Tailored Resume

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