Applied Data Scientist, Performance Marketing

Applied Data Scientist, Performance Marketing

This role is eligible for our hybrid work model: 2 days in-office

We’re a data-driven organization, which makes our Analytics and Data Science teams the brains of our operation. On the cutting edge of customer and business analytics, they make sure all our decisions and innovations are based on the latest insights.

As an Applied Data Scientist – Performance Marketing, you will play a key role in shaping and optimizing Priceline’s bidding strategies across platforms such as Google, Kayak, Tripadvisor, Trivago, and other major partners. You will design, build, and implement machine learning and statistical models that directly improve campaign performance, efficiency, and ROI in a fast-paced, dynamic, auction-based environment.

You will be responsible for translating business objectives into data science solutions, building and testing predictive models, and driving experimentation to improve bidding outcomes. As part of marketing, you will work closely with pricing, data, engineering, and product teams to implement models in production and continuously evolve our bidding stack.

Our marketing team manages billions of bids across multiple marketplaces every day, constantly refining strategies based on new signals and performance feedback. This role requires curiosity, experimentation, and the ability to find structure in a complex, data-rich, and sometimes messy environment.

• Design, develop, and deploy ML models for bid optimization and performance forecasting.

• Leverage statistical and causal inference methods (e.g., Bayesian modeling, uplift modeling) to improve decision-making.

• Continuously monitor model performance, retrain, and improve as needed.

• Analyze large, complex datasets to uncover patterns, insights, and optimization opportunities.

• Identify and build the right datasets and data pipelines required to support model development.

• Handle imperfect or fragmented data with structured problem-solving and creative data engineering approaches.

• Design and run A/B tests to evaluate model-driven bidding strategies.

• Apply causal inference to assess incremental impact and optimize future spend allocation.

• Partner with analysts and engineers to integrate experimentation frameworks into production systems.

• Collaborate with cross-functional teams (data, product & engineering) to identify business opportunities and prioritize projects.

• Translate technical insights into clear, actionable recommendations for stakeholders.

• Present model results and experimental outcomes to senior leaders and non-technical audiences.

• Work with stakeholders to identify clear opportunities to develop new approaches

• Prototype new approaches to bidding, automation, and signal integration.

• Continuously explore new modeling techniques, data sources, and partner APIs to improve outcomes.

• Contribute to building a scalable and modular ML infrastructure for digital marketing.

• 3–5 years of experience applying data science and machine learning to solve problems end-to-end.

• Hands-on experience with experimentation, causal inference, and Bayesian modeling.

• Proficiency in Python or R, with experience using ML libraries such as scikit-learn, XGBoost, PyTorch, or Tensor Flow.

• Strong data analysis and SQL skills; experience working with large datasets (Big Query, Spark, etc.).

• Proven ability to translate business goals into measurable data science solutions.

• Experience creating data pipelines or working with ETL processes.

• Excellent communication and collaboration skills; able to explain complex ideas simply.

• Curiosity, adaptability, and an impact-focused mindset, always striving to make a difference for our customers.

• A positive attitude toward change, and a strong sense of ownership and teamwork.

• Fluent English (verbal & written)

• Illustrated history of living the values necessary to Priceline:
  Customer, Innovation, Team, Accountability and Trust.

• The Right Results, the Right Way is not just a motto at Priceline;…