Senior Data Scientist - Real-Time Embeddings and DL

Jampp

United States

À distance

USD 125 000 - 210 000

Plein temps

14 jours+

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Résumé du poste

Jampp in the United States is seeking a Senior Data Scientist to design, develop, and deploy DNN-based models powering prediction and optimization in real‑time ad bidding. You will collaborate with ML, Data, and Software Engineers to turn research ideas into production‑grade solutions with measurable business impact.

The role focuses on embeddings, high-cardinality entities, and scalable ML infrastructure, enabling campaigns and placements to perform at scale.

Qualifications

  • 5+ years in data science or ML roles.
  • Strong quantitative background in a relevant field.
  • Proficient in Python and ML stack.
  • Experience with deep learning and large datasets.
  • Ability to productionize models with engineers.
  • Fluent English communication.

Responsabilités

  • Design, develop and iterate deep learning models for prediction and optimization.
  • Develop embedding-based approaches for high-cardinality entities.
  • Improve performance and generalization of ML models with raw signals and representations.
  • Experiment, evaluate results and translate successful experiments into production.
  • Design, code and deploy ML models and tools in Python.
  • Work with large-scale datasets and data pipelines to train and improve models.
  • Collaborate with ML, Data, and Software Engineers to ensure production readiness.
  • Analyze model metrics to understand impact on bidding and business outcomes.
  • Communicate findings and trade-offs clearly across teams.

Connaissances

Python
Deep Learning
Machine Learning
Data Science
English comms

Formation

Applied Math/Stats

Outils

Python ecosystem
TensorFlow/PyTorch

Description du poste

Jampp in the United States is seeking a Senior Data Scientist to design, develop, and deploy DNN-based models powering prediction and optimization in real‑time ad bidding. You will collaborate with ML, Data, and Software Engineers to turn research ideas into production‑grade solutions with measurable business impact.

The role focuses on embeddings, high-cardinality entities, and scalable ML infrastructure, enabling campaigns and placements to perform at scale.

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