Senior Data Scientist

TripleLift is hiring a Senior Data Scientist / Machine Learning Engineer in New York, NY (onsite) to help improve the performance of bidding algorithms and deliver scalable, production-ready machine learning systems. In this role, you’ll combine statistical analysis, experimentation, and ML engineering to turn market insights into measurable outcomes for TripleLift’s customers.

You’ll work within the Data Science team on problems that require both rigor and engineering discipline: designing and running experiments, analyzing market dynamics, and monitoring ML systems in production to ensure performance, reliability, and effectiveness. The team also emphasizes using the right tools for the job and continuously evaluating new technologies as needs evolve.

Responsibilities

• Design and run experiments that improve bidding algorithm performance and maximize customer outcomes.
• Use statistical analysis and advanced analytics to understand market dynamics and deliver actionable insights and recommendations.
• Develop, implement, and maintain scalable machine learning pipelines and systems with strong ML engineering best practices.
• Partner with engineering, product management, and business stakeholders to identify opportunities, solve challenges, and support data-informed decisions.
• Monitor and evaluate deep learning and machine learning systems to maintain performance and reliability in production.

Requirements

• A degree in a technical or quantitative field is preferred. Relevant professional experience and degrees in other disciplines will also be considered.
• 5+ years of professional experience in data science and/or machine learning in a collaborative work environment.
• 2+ years of professional experience developing data science and machine learning models in a programmatic advertising environment.
• Strong foundation in statistical analysis, deep learning, and machine learning.
• Hands-on experience with TensorFlow or PyTorch to prototype models for high-volume, distributed systems.
• Experience monitoring and measuring statistical model performance using tools such as Prometheus and Grafana, including building dashboards and alerts to detect performance issues and validate model effectiveness.
• Strong organizational skills, communication skills, and attention to detail.
• Ability to work efficiently and independently with minimal oversight.
• Openness to feedback and constructive criticism, with commitment to continuous learning and professional development.
• Strong work ethic and demonstrated commitment to delivering high-quality work.

Tools You’ll Work With

Python, Spark, Airflow, Databricks, ONNX, Docker, MySQL, Snowflake, Amazon S3, Parquet, AWS, TensorFlow, PyTorch, Scikit-learn, Prometheus, Grafana.

Compensation: USD 140,000 - 170,000 per year.