Senior Data Scientist

• Marketing Effectiveness: Lead scientific analysis across acquisition, lifecycle, audience strategy, channel performance, conversion, retention, and revenue.
• Experimentation: Design and evaluate randomized tests, holdouts, quasi-experimental studies, and incrementality analysis, with clear hypotheses, guardrails, power analysis, and decision criteria.
• Predictive Modeling: Build models for propensity, segmentation, next best action, churn, lifetime value, and campaign optimization that deliver measurable value.
• Attribution and Media Optimization: Connect channel, session, customer, and booking identifiers, separate factual reporting from modeled attribution, and feed offline conversions back to advertising platforms with privacy and consent built in.
• Funnel Measurement: Establish consistent metrics across brands and channels, from reach and engagement through bookings, revenue, and ROI.
• Data Quality and Instrumentation: Assess data across experimentation, customer, marketing automation, analytics, advertising, call center, and transactional sources, document limitations before results reach executives, and define instrumentation and identity requirements with engineering.
• Reusable Analytical Assets: Create datasets, features, and evaluation methods that enable trusted self-service analysis.
• Executive Communication: Explain findings, uncertainty, and tradeoffs in business language, linking recommendations to revenue and customer outcomes.
• Coaching and Standards: Coach analysts and partners on sound methods, reproducibility, and responsible AI.

• 7+ years applying data science, experimentation, statistics, or machine learning to complex business problems.
• Demonstrated expertise in experimental design and causal inference, plus predictive modeling, segmentation, forecasting, or optimization in production or decision-making settings.
• Advanced SQL and Python or R, with reproducible, production-quality analytical workflows.
• Experience with large, complex customer, digital behavior, campaign, or transaction datasets.
• Strong communication skills, including explaining methods and uncertainty to technical and executive audiences.
• Bachelor's degree in a quantitative field such as data science, statistics, mathematics, computer science, economics, or engineering. Master's or doctorate preferred. An equivalent combination of education and experience will be considered.

• Marketing science, advertising technology, or digital product analytics experience, including hands-on work with Statsig, Tealium, Marketo, GA4, advertising platforms, Power BI, or Microsoft Fabric.
• Identity resolution, multi-touch attribution, marketing mix modeling, incrementality testing, or offline conversion feedback, including privacy-aware measurement under GDPR and CCPA.
• Experience deploying and monitoring models with platform engineering teams, and establishing model governance and analytical standards.
• Background in travel, ecommerce, membership, or loyalty businesses with blended online and offline customer journeys.

arrivia powers travel loyalty and rewards programs for some of the world's leading brands. We help millions of travelers book memorable experiences while delivering the technology, supply, and service our partners build their programs on.

We are investing in growth and in the platform that drives it. Modern technology, data, and AI are changing how travel is sold and serviced, and we are building the systems and the teams to lead that shift rather than follow it.

Here at arrivia we…

• Stay Curious - Explore new challenges and make space to learn, grow and improve
• Keep it Real - Earn trust through open, honest and clear communication
• Own it - Seek ways to make an impact and take action
• Win Together - Create a culture of connection and inclusion where everyone can be their best