Senior Data Scientist

arrivia•Scottsdale, AZ

About The Position

arrivia is hiring a Senior Data Scientist to bring rigorous experimentation, predictive modeling, and decision science to our highest-value business problems. This is a new role on our growing data team, reporting to the VP of Data and AI Platform. Your focus starts with marketing technology and marketing effectiveness, including funnel measurement, attribution, audience intelligence, personalization, and experimentation. From there, your work extends into enterprise priorities across travel products, customer experience, finance, and operations. This is a senior individual contributor role with real autonomy. You will own a prioritized backlog from problem framing through deployment, decide which methods fit the question, and say plainly when the data will not support the conclusion someone wants. The work directly influences marketing investment and customer targeting across our brands.

Requirements

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.

Nice To Haves

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.

Responsibilities

Lead scientific analysis across acquisition, lifecycle, audience strategy, channel performance, conversion, retention, and revenue.
Design and evaluate randomized tests, holdouts, quasi-experimental studies, and incrementality analysis, with clear hypotheses, guardrails, power analysis, and decision criteria.
Build models for propensity, segmentation, next best action, churn, lifetime value, and campaign optimization that deliver measurable value.
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.
Establish consistent metrics across brands and channels, from reach and engagement through bookings, revenue, and ROI.
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.
Create datasets, features, and evaluation methods that enable trusted self-service analysis.
Explain findings, uncertainty, and tradeoffs in business language, linking recommendations to revenue and customer outcomes.
Coach analysts and partners on sound methods, reproducibility, and responsible AI.