As a Senior Data Scientist at Coinbase, you'll leverage your expertise to enhance customer experience across various consumer products by conducting deep analyses and translating insights into actionable strategies.
Senior Product Data Scientist
π Description
- Lead the development of Data Science within Product, producing statistical models that impact product insights and recommendations.
- Scale the impact of the Product Analytics team through automation and self-service model capabilities.
- Architect and implement sophisticated statistical models to enhance product features like personalization.
- Explore new tooling and approaches, including Agentic AI, to identify opportunities and drive adoption.
- Partner with cross-functional teams to identify high-impact opportunities for data science.
- Champion experimentation by designing and analyzing complex AB tests and causal inference models.
π οΈ Requirements
- Experience: Significant experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization.
- Product Acumen: Demonstrated ability to define, implement, and operationalize crucial product and feature-level metrics from scratch.
- Strategic Influence: A 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 teams).
- Scaling Impact: Experience scaling your impact through the creation of automated processes, self-service tools, or data products.
- 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.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 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.
- Deep experience in developing sophisticated customer segmentation models including predictive LTV modeling.
Full job description
About Tripadvisor
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the worldβs most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork.
At Tripadvisor experiences, the only thing we love more than travel is data. We slice it, we dice it, and we use it to empower our decision making.
About the Role
As our Senior Product Data Scientist, you will be the cornerstone of our advanced analytics capability.
This is more than a technical role; it's a high-impact position designed to shape the future of our product by embedding deep, quantitative intelligence into its core.
You will help set the vision for how data science can solve our most challenging problems.
You will act as a catalyst, mentoring a talented team of product analysts while spearheading the development of models and frameworks that drive our product strategy forward.
What You will do:
- Lead the development of Data Science within Product, producing statistical models that directly impact the insights and recommendations that drive the product and customer experience.
- Use your knowledge and experience to help scale the impact of the Product Analytics team through data science. Creating automation, self service model capability, improve experimentation velocity, and drive efficiency.
- Architect and implement sophisticated statistical models (predictive, classification, clustering, etc.) to enhance product features like personalization and recommendations.
- Exploration of new tooling, product and approaches including Agentic AI and AI Agents, to identify opportunity areas, explore through POC to then drive to adoption.
- Partner with Product Managers, Designers, and Engineers to identify high-impact opportunities where data science can solve customer problems and improve the product.
- Champion experimentation by designing and analyzing complex AB tests, causal inference models, and uplift modeling to inform product decisions.
- Guide and mentor other product analysts in best practices for experimentation, modeling, and data-driven product development upskilling the team and defining the roadmap for Product Data Science.
- Communicate complex data insights to both technical and non-technical stakeholders with clarity and influence.
Skills & Experience:
- Experience: Significant experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization.
- Technical & Modeling Expertise: Advanced 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).
- Product Acumen: Demonstrated ability to define, implement, and operationalize crucial product and feature-level metrics from scratch.
- Strategic Influence: A 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 teams).
- Scaling Impact: Experience scaling your impact through the creation of automated processes, self-service tools, or data products.
- 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.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Nice to Haves:
- 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.
- Deep experience in developing sophisticated customer segmentation models including predictive LTV modeling.
- Experience working within a two-sided marketplace, e-commerce, or the travel technology industry.
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!
#LI- Remote
#LI-SM1
Similar jobs
Search more Data Scientist jobsAs a Data Scientist at Dataiku, you will develop solutions to real-world problems, support clients in mastering the platform, and co-develop data science projects.
Senior Applied Data Scientist, Fleet Intelligence
As a Senior Applied Data Scientist, you will leverage fleet maintenance and operational data to develop actionable intelligence, enhancing decision-making on usage, costs, and maintenance risks.
As a Senior Data Scientist, you will develop advanced machine learning models for real-time optimization in the programmatic advertising ecosystem, impacting large-scale production systems.
Senior Data Scientist (German-speaking)
As a Senior Data Scientist at Dataiku, you will develop solutions to real-world problems, support clients throughout their journey, and mentor others in data science practices.
