Role Description As a Principal Product Data Scientist, you will operate as the most senior technical leader in the Product Data Science function. You will shape the vision, set the technical direction, and drive strategic impact through innovative analytical solutions. This role is both highly technical and deeply collaborative, requiring excellence in leadership, communication, and cross-functional influence. - 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. Qualifications - Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization. - 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). - Demonstrated ability to define, implement, and operationalize crucial product and feature-level metrics from scratch. - 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). - Experience scaling analytics capabilities, driving impact through the creation of automated processes, self-service tools, or data products. - Leader in critical thinking, demonstrating 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. - Outstanding leadership skills, with experience in mentoring, coaching, and developing teams of analysts or data scientists. - Exceptional collaboration and communication skills, with the ability to engage, influence, and inspire cross-functional partners at all levels. - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Requirements - 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. - Mastser's degree or equivalent relevant programs. Benefits - 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 AccessibleRecruiting@tripadvisor.com. - If you have any additional questions about careers at Tripadvisor you can email us at recruitment@tripadvisor.com. We have all the answers!

• Assist TSD with data analytic products by providing highly skilled and authoritative expertise on analytic methods. • Perform data quality analysis on source tables to identify any abnormalities or inconsistencies. • Review, maintain, and provide support using all existing fraud indicators developed by TSD. • Develop and refine repeatable processes for efficiently combining and analyzing large data sources (including relational tables, structured and unstructured datasets). • Collaborate closely with criminal investigators to determine and execute strategies to support cases; proactively address and communicate potential data quality issues and adapt analysis to shifting case needs; adhere closely to federal rules of criminal procedure governing protected information (e.g., Rule 6(e)). • Design, develop, and implement advanced statistical and machine learning models targeted at identifying fraud, improper payments, or non-compliance within SBA programs. • Utilize indicators of potential fraud, improper payments, or non-compliance to develop and test predictive models. • Assist in developing case leads for SBA OIG investigations based on model outcomes. • Coordinate with the Data Engineering Team to ensure system architecture is designed to efficiently support machine learning models. • Integrate and scale natural language processing methods to parse, clean, and analyze large corpora of unstructured or semi-structured text data, utilizing OCR, semantic similarity algorithms, and large language models as needed. • Provide detailed documentation of all methodology, test models, and production models; maintain records in compliance with criminal evidentiary requirements. • Develop visualizations and dashboards to demonstrate methodological choices, outcomes, and predictive capabilities of machine learning models; iteratively solicit and integrate end-user feedback. • Provide outcomes and recommendations in multiple formats, including data summaries and visualizations for investigative staff, and executive summaries for SBA OIG leadership. • Create programming and automation techniques to improve task efficiency using tools such as SharePoint, Python, Microsoft Excel, Power BI, and others. • Identify new business questions to expand the scope of analysis and reporting.

• Build a comprehensive map of the decision-making chain within target clients • Drive partnership upgrades with Nvidia or OpenAI and Colo clients through joint POCs • Align technical roadmap and solutions to client needs • Identify alignment opportunities for Midea’s cooling solutions

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency. • This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis. • You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS. • Deliver buying models that maintain positive ROAS and quality. • Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth. • Establish trusted, direct partnership with vertical business stakeholders. • Produce trusted output: validated, documented, low correction burden. • Identify and leverage net-new modeling opportunities the business has not flagged.