Head of Data Science: Embeddings & Audience Intelligence

Jobtome; Tenafly (NJ); On-site; USD 263,000 - 394,000; Full time

Job summary

Spectrum is seeking a Head of Data Science in New York City to lead the embedding, modelling, and measurement work powering our AI-native platform. You will build predictive models, own audience definitions, and direct the embedding roadmap with external partners to deliver commercial value.

In this in-office role, you’ll lead a cross-functional data science team, establish MLOps and responsible AI standards, and work with product and sales to scope pilots and convert evaluations into contracts.

Qualifications

• Proven track record leading data science for audience/measurement products.
• Hands-on predictive modeling on consumer data at scale.
• Experience with identity graphs and data collaboration tools.

Responsibilities

• Build predictive models for audiences and data products.
• Own segment definitions, coverage, and accuracy for audiences.
• Lead the platform's Feature Store as a commercial product.
• Lead evaluation and responsible AI standards across models.
• Define the embedding model roadmap with external partners.
• Establish MLOps and privacy-preserving analytics standards.
• Lead and grow a data science team and recruit senior talent.
• Represent data science in customer and partner discussions.

Skills

Data science leadership

Predictive modeling

Measurement & causal inference

Identity data & onboarding

Feature stores & pipelines

Python / SQL

Deep learning & embeddings

Privacy-preserving analytics

Executive communication

Team building

Education

Bachelor's in CS/Statistics

Master/PhD preferred

Tools

Snowflake

Databricks

AWS

LiveRamp

RampID/UID2

Job description

Spectrum is seeking a Head of Data Science in New York City to lead the embedding, modelling, and measurement work powering our AI-native platform. You will build predictive models, own audience definitions, and direct the embedding roadmap with external partners to deliver commercial value.

In this in-office role, you’ll lead a cross-functional data science team, establish MLOps and responsible AI standards, and work with product and sales to scope pilots and convert evaluations into contracts.