Head of Data Science — Embedding & Commercial ML

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

Job summary

Spectrum is seeking a Head of Data Science to build and lead the data science team responsible for the platform's transformer-based embedding model and predictive analytics. You will own measurement, audience segmentation, and data collaboration, working with product, sales, and external partners to scope pilots and convert evaluations into contracts.

You will establish responsible AI standards, MLOps practices, and a data-driven culture focused on production deployment and revenue impact.

Qualifications

• Experience leading applied data science or analytics teams
• Hands-on predictive modeling on consumer-level data at scale
• Strong understanding of measurement, uplift, and attribution methods
• Familiarity with privacy-preserving analytics and data governance

Responsibilities

• Build predictive models for audience and data products across multiple verticals
• Own segment definitions, coverage, and accuracy for audiences
• Lead the platform's Feature Store as a commercial product
• Define and defend the platform's measurement methodology and validation
• Direct the roadmap for the embedding model and ensure production readiness
• Establish MLOps, evaluation standards, and responsible AI practices
• Lead a data science team including ML engineers and researchers
• Engage with customers and partners to translate methodology into commercial proof points

Skills

Predictive modeling

Measurement & causal inference

Identity & data collaboration

Python

SQL

Spark / distributed processing

Education

Bachelor's Degree in CS/Stats/Math/Economics or related field

Master's or PhD preferred

Tools

Snowflake

AWS

LiveRamp

Feature stores

Job description

Spectrum is seeking a Head of Data Science to build and lead the data science team responsible for the platform's transformer-based embedding model and predictive analytics. You will own measurement, audience segmentation, and data collaboration, working with product, sales, and external partners to scope pilots and convert evaluations into contracts.

You will establish responsible AI standards, MLOps practices, and a data-driven culture focused on production deployment and revenue impact.