Senior Data Scientist / Machine Learning Engineer

About the role

TripleLift is a creative SSP that brings together creative, supply, audience and measurement into a single outcome-driven system across the open internet, retail media and CTV. The Data Scientist / Machine Learning Engineer improves the performance of TripleLift's bidding algorithms and builds scalable machine learning solutions. The role combines statistical analysis, experimentation and ML engineering, partnering with engineering, product management and business stakeholders to turn data-driven insights into measurable results.

Key responsibilities

• Design and run experiments to improve bidding algorithm performance and customer outcomes.
• Apply statistical analysis and advanced analytics to understand market dynamics and deliver actionable insights.
• Develop, implement and maintain scalable, production-ready machine learning pipelines and systems.
• Collaborate with engineering, product and business teams to identify opportunities and drive data-informed decisions.
• Monitor and evaluate deep learning and machine learning systems in production for performance and reliability.

Required profile

• A degree in a technical or quantitative field is preferred; candidates with relevant experience in other fields will also be considered.
• At least five years of professional experience in data science and/or machine learning.
• At least two years of experience developing data science and ML models in a programmatic advertising environment.
• Strong foundation in statistical analysis, deep learning and machine learning.
• Hands-on experience prototyping models with TensorFlow or PyTorch for high-volume, distributed systems.
• Experience monitoring model performance with tools such as Prometheus and Grafana, including dashboards and alerts.
• Ability to work independently with minimal oversight and openness to feedback.

Required skills

• Python
• Spark, Airflow, Databricks, ONNX, Docker
• MySQL, Snowflake, Amazon S3, Parquet
• Amazon Web Services (AWS)
• TensorFlow, PyTorch, Scikit-learn, Spark
• Prometheus, Grafana