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AI Lookalike Audience Modeling Developer

Lucas Sato

Full-time · Job · New_York

About the role

The best customers you have not found yet look like your best customers. Lookalike modeling — building audience segments that share behavioral and demographic signatures with high-value existing customers — is one of the most reliable levers in performance marketing. Done well, it can halve customer acquisition cost. Done poorly, it creates audiences that look similar on paper but behave completely differently in practice. We build growth marketing intelligence for 180 DTC brands. Our lookalike modeling system builds audience seeds from CRM customer data, generates behavioral and firmographic similarity scores against external data sources, and produces audiences that integrate directly with Meta, Google, and programmatic buying platforms. You will own the similarity modeling layer: designing the embedding space that represents customer characteristics, improving the matching quality for cold-start brands with small seed audiences, and building the outcome tracking that measures whether lookalike audiences actually convert at better rates.

Responsibilities

  • Build customer embedding models for lookalike audience seed representation
  • Design similarity scoring against external behavioral and firmographic data sources
  • Improve matching quality for brands with small seed audiences under 1,000 customers
  • Implement audience export integrations for Meta, Google, and programmatic platforms
  • Build conversion outcome tracking to measure lookalike audience quality
  • Create audience quality scoring that predicts conversion rates before campaign launch

Requirements

  • 3+ years in ML engineering with marketing analytics or audience modeling experience
  • Experience with embedding models, similarity search, or lookalike modeling systems
  • Strong Python, SQL, and Spark skills for large-scale audience data processing
  • Familiarity with digital advertising platforms and audience targeting concepts
  • Understanding of privacy constraints and data clean room approaches

Benefits

  • Fully remote
  • Health and dental
  • $3,000 professional development budget
  • Performance bonus
  • Equity participation

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI Business, Marketing & Strategy data science & analytics

Skills

python pytorch sql spark statistics pandas

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