Head of Data Science — Embeddings & AI Platform Lead

Jobtome; Village of Westbury (NY); On-site; USD 263,000 - 394,000; Full time

Job summary

Spectrum seeks a Head of Data Science in New York to lead a team building transformer-based embeddings and predictive models for audiences, insights, and measurement products. You will set evidence standards, scope pilots with product and sales, and translate methodology into commercial proof points.

You will own the embedding roadmap, define MLOps and privacy controls, collaborate with Legal and Privacy, and drive production deployment with clear revenue impact.

Qualifications

• Proven record leading data science for data, audience, identity, or measurement products.
• Hands-on predictive modeling on consumer-level data at scale.
• Strong grounding in measurement and causal inference.
• Familiarity with privacy-preserving analytics and regulation.
• Ability to explain methodology to executives and buyers.

Responsibilities

• Lead a data science team of scientists and ML engineers.
• Own embedding model roadmap and platform features.
• Define MLOps, evaluation standards, and release gates.
• Partner with product, sales, and Legal to ensure commercial impact.
• Design measurement methodology and propagation to revenue.

Skills

Predictive modeling

Measurement & causal inference

Identity/data collaboration

ML lifecycle

Python

SQL

Distributed processing

Deep learning/embeddings/ transformers

Privacy-preserving analytics

Leadership of data science teams

Education

Bachelor's degree in CS/Statistics/Math/Economics

Master's or PhD preferred in quantitative field

Tools

Snowflake

LiveRamp

AWS

Databricks

Spark

Job description

Spectrum seeks a Head of Data Science in New York to lead a team building transformer-based embeddings and predictive models for audiences, insights, and measurement products. You will set evidence standards, scope pilots with product and sales, and translate methodology into commercial proof points.

You will own the embedding roadmap, define MLOps and privacy controls, collaborate with Legal and Privacy, and drive production deployment with clear revenue impact.