<strong>Senior Data Scientist, Revenue Management Systems </strong><br><br><strong>Job Summary:</strong><br><br>Viking is scaling its Revenue Management System (RMS) from a successful MVP to full inventory coverage and sustained yield uplift. This role serves as the hands-on technical lead for the RMS analytics engine owning the suite of machine-learning models, setting methodological direction, and making pragmatic decisions about when to use (or not use) ML.<br><br>The Lead Data Scientist sits embedded with the Yield team (business) while partnering daily with Technology (data engineering, front-end, MLOps) to ensure the RMS remains stable, fast, explainable, and tightly aligned with business needs.<br><br>This is a hybrid position based in our Woodland Hills, CA office. You will be required to adhere to our hybrid work policy, working from our office Monday and Thursday plus one additional weekday on a weekly basis.<br><br><strong>Job Responsibilities</strong><strong>:</strong><br><ul><li><strong>Own the RMS analytics engine end-to-end: </strong>demand forecasting, cancellations, price optimization, and recommendation logic-including data prep, training, validation, deployment, monitoring, documentation, and on-time retrains.</li><li><strong>Improve reliability, coherence, and trust:</strong> by refining constraints, features, guardrails, and business rules; reducing edge-case behaviors; strengthening monitoring, drift detection, and recovery playbooks; and improving model response times.</li><li><strong>Drive adoption and business impact: </strong> by partnering with Yield and Front-End to expand RMS-managed sailing coverage, ensure outputs are actionable in the tool, and track yield uplift versus control.</li><li><strong>Lead high-value experimentation:</strong> by defining hypotheses, offline evaluation frameworks (IPS/DR), shadow tests, guardrails, and safe on-policy trials; promote winning changes to production with rollback plans.</li><li><strong>Embed with Yield stakeholders:</strong> to translate pricing and inventory strategy into model logic and constraints, explain drivers of recommendations, and present results in clear business terms.</li><li><strong>Ensure strong production hygiene & MLOps:</strong> in partnership with Data Engineering/DevOps, including CI/CD, pipeline health, retraining orchestration, versioning, and feature-store usage.</li><li><strong>Champion pragmatic, right-sized solutions: </strong>using rules, SQL, or heuristics where signal, latency, governance, or explainability make ML unsuitable.</li><li><strong>Strengthen explainability & documentation:</strong> by upgrading care-and-feeding guides, methodology docs, and analyst manuals, lead knowledge transfer as external support tapers.</li></ul><br><br><strong>Success Metrics:</strong><br><ul><li><strong>Coverage:</strong> Increasing percentage of sailings price-managed by RMS quarter-over-quarter.</li><li><strong>Yield Uplift:</strong> Stable, measurable uplift vs. control groups with well-documented drivers and explainers.</li><li><strong>Quality & Speed:</strong> Reduction in edge-case incidents, improved model response times, increased analyst trust and recommendation acceptance rates.</li><li><strong>Operational Hygiene:</strong> On-time retrains, green pipeline SLAs, and zero critical incidents attributable to model logic.</li></ul><br><strong>Job Requirements</strong><strong>:</strong><br><ul><li>6+ years of experience delivering production-grade, commercially impactful ML solutions. </li><li>Preferred experience in pricing, forecasting, or inventory optimization within travel or hospitality.</li><li>Expert proficiency in Python, SQL, Spark, Databricks, and production ML practices (versioning, feature stores, monitoring, CI/CD).</li><li>Strong foundation in constrained optimization, experimental design, time-series modeling, causal inference, and interpretable ML techniques.</li><li>Demonstrated success shipping ML features into user-facing tools and collaborating with business owners.</li><li>Exceptional communication skills with the ability to explain complex concepts simply and defend methodological choices.</li></ul><br><br><strong>What We Offer You</strong><strong>:</strong><br><ul><li>Highly competitive compensation plan. </li><ul><li>Salary range $200,000-$220,000 annually determined by a myriad of factors including, but not limited to, years of experience, depth of experience, and other relevant business considerations.</li><li>Employees are eligible for annual discretionary bonus.</li><li>401(k) plan with company match.</li><li>Employee Share Purchase Plan (ESPP) Viking full-time regular employees working in the United States can purchase Viking shares through payroll deductions.</li></ul><li>Full benefits including medical, dental, vision, life and disability insurance at a highly subsidized rate (some plans are fully paid by Viking).</li><li>Accrue 15 paid vacation days, sick time accrual by state, and 6 paid holidays per year.</li><li>Opportunity to take a free and/or discounted cruise.</li><li>Highly subsidized gym membership.</li><li>Discounts on theatres, theme parks, movie tickets, travel discounts through IATA membership and too many more discounts to name.</li></ul><br><strong>Viking is a certified Great Place to Work company. This certification is a result of our commitment to excellence, integrity and our teams' outstanding contributions.</strong><br><br><strong>About Viking</strong><br><br>Viking was founded in 1997 and provides destination-focused voyages on oceans, rivers and lakes around the world. Designed for experienced travelers with interests in science, history, culture and cuisine, Chairman Torstein Hagen often says Viking offers experiences for The Thinking Person®.<br><br>Viking has more than 250 awards to its name, including being rated #1 for Rivers, #1 for Oceans and #1 for Expeditions by Condé Nast Traveler and voted at the top of its categories by Travel + Leisure. No other cruise line has ever received these same honors by both publications at the same time.