Senior Data Scientist - ML Engineer for Scalable Bidding

TripleLift; Zurich (KS); On-site; USD 120,000 - 180,000; Full time

Job summary

TripleLift is seeking a Data Scientist / Machine Learning Engineer to improve bidding algorithms and build scalable ML solutions across our platform. You will partner with engineering, product management, and business stakeholders to translate data-driven insights into measurable impact.

The role requires strong statistical analysis, deep learning expertise, and hands-on experience with TensorFlow or PyTorch to prototype models for high-volume, distributed systems. Collaboration is key.

Qualifications

• A degree in a technical or quantitative field is preferred.
• At least five years of professional experience in data science and/or machine learning.
• At least two years of professional experience in a programmatic advertising environment.

Responsibilities

• Design and run experiments to improve bidding algorithm performance.
• Apply statistical analysis to understand market dynamics and deliver actionable insights.
• Develop, implement, and maintain scalable, production-ready ML pipelines and systems.
• Collaborate with engineering, product management, and business stakeholders to identify opportunities and drive data-informed decisions.
• Monitor and evaluate ML systems to ensure performance and reliability in production environments.

Skills

Python

Statistical analysis

Machine learning

Deep learning

Five years of experience

Education

Engineering degree in a technical field

Tools

Python

Spark

Airflow

Databricks

ONNX

Docker

TensorFlow

PyTorch

Scikit-learn

Prometheus

Grafana

Job description

TripleLift is seeking a Data Scientist / Machine Learning Engineer to improve bidding algorithms and build scalable ML solutions across our platform. You will partner with engineering, product management, and business stakeholders to translate data-driven insights into measurable impact.

The role requires strong statistical analysis, deep learning expertise, and hands-on experience with TensorFlow or PyTorch to prototype models for high-volume, distributed systems. Collaboration is key.