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About the Role
The Data Scientist / Machine Learning Engineer plays a critical role in improving the performance of TripleLift’s bidding algorithms and developing scalable machine learning solutions that drive better outcomes for our customers. This role combines statistical analysis, experimentation, and machine learning engineering to uncover market insights, optimize bidding performance, and build production-ready systems. You will partner closely with engineering, product management, and business stakeholders to identify opportunities, test hypotheses, and translate data-driven insights into measurable business impact.
Responsibilities
- Design and run experiments to improve bidding algorithm performance and maximize outcomes for TripleLift’s customers.
- Apply statistical analysis and advanced analytics techniques to understand market dynamics and deliver actionable insights and recommendations.
- Develop, implement, and maintain scalable, production-ready machine learning pipelines and systems, applying best practices in ML engineering.
- Collaborate with engineering, product management, and business stakeholders to identify opportunities, solve challenges, and drive data-informed decisions.
- Monitor and evaluate deep learning and machine learning systems to ensure performance, reliability, and effectiveness in production environments.
Requirements
- A degree in a technical or quantitative field is preferred. Candidates with relevant professional experience and degrees in other disciplines will also be considered.
- At least five years of professional experience in data science and/or machine learning within a collaborative work environment.
- At least two 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 techniques.
- 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 identify performance issues and ensure models function effectively.
- Strong organizational, communication, and attention-to-detail skills.
- Ability to work efficiently and independently with minimal oversight.
- Openness to feedback and constructive criticism, with a commitment to continuous learning and professional development.
- Strong work ethic and a demonstrated commitment to delivering high-quality work.
Skills
- Python
- Spark
- Airflow
- Databricks
- ONNX
- Docker
- MySQL
- Snowflake
- Amazon S3
- Parquet
- Amazon Web Services (AWS)
- TensorFlow
- PyTorch
- Scikit-learn
- Prometheus
- Grafana
Experience Level
- At least five years of professional experience in data science and/or machine learning
- At least two years of professional experience developing data science and machine learning models in a programmatic advertising environment
Education Level
- A degree in a technical or quantitative field is preferred.
About the Company
- TripleLift is the Creative SSP powered by TL Spark, our agentic intelligence layer. We orchestrate creative, supply, audience, and measurement into a single outcome-driven system across the open internet, retail media, and CTV. Our platform enables brands and agencies to drive measurable performance while helping publishers maximize yield and preserve high-quality user experiences.
- At TripleLift, we believe great work starts with great people. We foster a culture built on collaboration, curiosity, and a shared commitment to making each other better. We move with urgency, challenge convention, and continuously innovate to elevate digital advertising. We value people who bring new perspectives, take ownership, and work together to drive meaningful impact. Learn more about TripleLift and our culture on our LinkedIn Life page.