Head of Data Science — Embeddings & Commercial Impact

Jobtome; Village of Great Neck (NY); Vor Ort; USD 263.000 - 394.000; Vollzeit

Zusammenfassung

Spectrum Intelligence Ventures in New York City seeks a Head of Data Science to lead predictive modeling, embedding development, and measurement across the platform. You will define evaluation standards, anchor the embedding roadmap with external partners, and collaborate with product and sales to scope pilots and convert evaluations into commercial contracts.

You will build and lead a data science team, establish responsible AI and MLOps standards, and ensure privacy-preserving analytics while

Qualifikationen

• Proven record leading data science for data, audience, identity, or measurement products.
• Hands-on predictive modeling on large-scale consumer data.
• Strong grounding in measurement and causal inference.

Aufgaben

• Build and run predictive models for audience and data products across multiple verticals.
• Own segment definitions, coverage, refresh cadence, and accuracy for all audiences.
• Lead the platform's transformer-based embedding model and its evaluation standards.
• Establish MLOps, release gates, drift monitoring, and privacy-preserving techniques.
• Lead a data science team and drive production deployment with revenue impact.

Kenntnisse

Predictive modeling

Measurement & causal inference

MLOps & production

Python

SQL

Spark

Snowflake

AWS

Embeddings & transformers

Team leadership

Ausbildung

Bachelors in CS/Statistics/Math/Economics

Tools

Python

SQL

Spark

Snowflake

Databricks

AWS

LiveRamp

Jobbeschreibung

Spectrum Intelligence Ventures in New York City seeks a Head of Data Science to lead predictive modeling, embedding development, and measurement across the platform. You will define evaluation standards, anchor the embedding roadmap with external partners, and collaborate with product and sales to scope pilots and convert evaluations into commercial contracts.

You will build and lead a data science team, establish responsible AI and MLOps standards, and ensure privacy-preserving analytics while