Tripadvisor - Principal Product Data Scientist
Requirements
• Experience: Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization. • Technical & Modeling Expertise: Expert Level proficiency in Python and SQL. Deep, hands-on experience with statistical modeling, (quasi) experimentation, multi-arm bandit, and a wide range of machine learning techniques (e.g., Regression, Classification, Clustering). • Technical & Modeling Expertise: • Python and SQL • Product Acumen: Demonstrated ability to define, implement, and operationalize crucial product and feature-level metrics from scratch. • Product Acumen: • Strategic Influence: A proven track record of driving strategic impact through proactive and collaborative approach with the proven ability to lead technical discussions, drive product strategy, and communicate complex insights effectively to cross-functional partners (e.g., Product, Engineering, Design). • Strategic Influence: • Scaling Impact: Experience scaling analytics capabilities, driving impact through the creation of automated processes, self-service tools, or data products. • Scaling Impact: • Critical Thinking: Leader in critical thinking, your previous experience will demonstrate the analysis of available facts, evidence, observations, and arguments in order to form a judgment by the application of rational, skeptical, and unbiased analyses and evaluation. • Critical Thinking: • Leadership: Outstanding leadership skills, with experience in mentoring, coaching, and developing teams of analysts or data scientists. • Leadership: • Collaboration & Communication: Exceptional collaboration and communication skills, with the ability to engage, influence, and inspire cross-functional partners at all levels. • Collaboration & Communication: • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. • You could be an especially great fit if you have: • Advanced programming background with the ability to build simulations and prototype data products. • Experience validating quantitative findings with qualitative methods (e.g., surveys, user research). • Demonstrated experience with applied AI, such as NLP, Large Language Models (LLMs), or Agentic AI for analytics. • Experience working within a two-sided marketplace, e-commerce, or the travel technology industry. • Masters degree or equivalent relevant programs • We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at [email protected]. • [email protected] • If you have any additional questions about careers at Tripadvisor you can email us at [email protected]. We have all the answers! • [email protected]
Responsibilities
• Lead and define the Data Science strategy for Product, ensuring that advanced analytics, data science, and AI methodologies are central to how we build great products and improve customer experiences. • Serve as a trusted strategic advisor to senior Product and Engineering leadership, ensuring that data-driven decision making is embedded at the highest levels of the organization. • Drive the development and adoption of next-generation data science tooling, platforms, and frameworks, with a focus on automation, scalability, and reproducibility. • Spearhead the exploration and integration of emerging AI technologies, such as Agentic AI and AI Agents, identifying and developing high-impact use cases from POC to production. • Champion best practices in experimentation, causal inference, and uplift modeling, ensuring statistical rigor in decision-making processes. • Take ownership of the most complex, high-profile analytical projects, translating ambiguous questions into clear, actionable recommendations that deliver commercial and customer value. • Mentor, coach, and develop other Data Scientists and Analysts, fostering a culture of critical thinking, continuous learning, and technical excellence. • Lead initiatives to scale impact through automation, self-service, and democratization of data science capabilities. • Develop sophisticated customer segmentation, and predictive models that directly inform and optimize the product roadmap. • Communicate complex analytical and technical concepts to diverse audiences, influencing stakeholders across Product, Engineering, Design, and Commercial teams.
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