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AI User Lifetime Value Modeling Engineer

Aaliyah Okafor

Full-time · Job · New_York

About the role

How much should you spend to acquire a user you've never seen before? If your LTV model can answer that question in the first 3 days of a user's lifecycle — before they've given you much behavioral signal — you can make acquisition decisions that the competition can't. Our personalization platform's growth depends on LTV prediction. We use it for acquisition bid optimization, churn intervention prioritization, and upsell timing decisions across 12 consumer app clients. The current model is a survival model with engineered features that reaches its accuracy ceiling at Day 7. We need to push that ceiling back to Day 3 using behavioral embedding approaches that extract more signal from early user actions. You'll redesign the early-LTV prediction system from the ground up, exploring sequence models and contrastive learning techniques that have shown promise in adjacent domains. You'll validate against out-of-sample cohorts and deploy to production serving 40 million user predictions per day.

Responsibilities

  • Redesign early-LTV prediction using behavioral embedding and sequence modeling
  • Implement contrastive learning approaches for sparse early-lifecycle user data
  • Build out-of-sample validation frameworks across different client apps and cohorts
  • Deploy production prediction serving for 40 million daily user predictions
  • Partner with growth teams at client companies to calibrate model to their objectives
  • Monitor for model drift across user cohorts and seasonal patterns

Requirements

  • 5+ years in ML engineering with consumer product analytics experience
  • Experience with survival models, customer lifetime value, or churn prediction
  • Strong PyTorch skills and familiarity with sequence modeling
  • Production experience serving predictions at tens of millions of daily requests
  • Ability to work across client relationships with different business objectives

Benefits

  • Fully remote
  • Competitive compensation
  • Health, dental, and vision
  • Equity package
  • Quarterly company performance bonus

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Categories

data science & analytics AI Business, Marketing & Strategy

Skills

python pytorch statistics sql spark

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Job Type

Full-time

Level

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Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics AI Business, Marketing & Strategy

Skills

python pytorch statistics sql spark pandas

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