Senior Data Scientist, Revenue Management Systems

Senior Data Scientist, Revenue Management Systems

Join us to apply for the Senior Data Scientist, Revenue Management Systems role at Viking
.

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.

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.

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.

• Own the RMS analytics engine end‑to‑end: demand forecasting, cancellations, price optimization, and recommendation logic—including data prep, training, validation, deployment, monitoring, documentation, and on‑time retrains.
• Improve reliability, coherence, and trust by refining constraints, features, guardrails, and business rules; reducing edge‑case behaviors; strengthening monitoring, drift detection, and recovery playbooks; and improving model response times.
• Drive adoption and business impact 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.
• Lead high‑value experimentation by defining hypotheses, offline evaluation frameworks (IPS/DR), shadow tests, guardrails, and safe on‑policy trials; promote winning changes to production with rollback plans.
• Embed with Yield stakeholders to translate pricing and inventory strategy into model logic and constraints, explain drivers of recommendations, and present results in clear business terms.
• Ensure strong production hygiene & MLOps in partnership with Data Engineering/Dev Ops, including CI/CD, pipeline health, retraining orchestration, versioning, and feature‑store usage.
• Champion pragmatic, right‑sized solutions using rules, SQL, or heuristics where signal, latency, governance, or explainability make ML unsuitable.
• Strengthen explainability & documentation by upgrading care‑and‑feeding guides, methodology docs, and analyst manuals; lead knowledge transfer as external support tapers.

• Coverage:
  Increase the percentage of sailings price‑managed by RMS quarter‑over‑quarter.
• Yield Uplift:
  Achieve stable, measurable uplift vs. control groups with well‑documented drivers and explainers.
• Quality & Speed:
  Reduce edge‑case incidents, improve model response times, and increase analyst trust and recommendation acceptance rates.
• Operational Hygiene:
  Deliver on‑time retrains, green pipeline SLAs, and zero critical incidents attributable to model logic.

• 6+ years of experience delivering production‑grade, commercially impactful ML solutions.
• Preferred experience in pricing, forecasting, or inventory optimization within travel or hospitality.
• Expert proficiency in Python, SQL, Spark, Databricks, and production ML practices (versioning, feature stores, monitoring, CI/CD).
• Strong foundation in constrained optimization, experimental design, time‑series modeling, causal inference, and interpretable ML techniques.
• Demonstrated success shipping ML features into user‑facing tools and collaborating with business owners.
• Exceptional communication skills with the ability to explain complex concepts simply and defend methodological choices.

• Highly competitive compensation plan.
  • Salary range $200,000‑$220,000 annually, determined by a myriad of factors including years of experience and other relevant business considerations.
  • Employees are eligible for an annual discretionary bonus.
  • 401(k) plan with company match.
  • Employee Share Purchase Plan (ESPP) for full‑time employees working in the United States.
• Full benefits including medical, dental, vision, life and disability insurance…