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Remote Hotel Optimization Jobs (NOW HIRING)

Remote Position with occasional travel to the Corporate Office Employment Type: Full Time Company ... Rebel Hotel Company is one of the fastest-growing third-party hotel management companies in the ...

... Hotels to accelerate releases by up to 75%, reduce cloud costs by up to 60%, and achieve 10x DevOps ... Remote within the U.S or Hybrid from one of our U.S offices. What you will have at Harness

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Remote Hotel Optimization information

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$40

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$81

How much do remote hotel optimization jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for remote hotel optimization in the United States is $59.65, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $73.56 per hour, depending on experience, location, and employer.

What is a remote hotel optimization specialist?

A Remote Hotel Optimization specialist is a professional who works remotely to improve the performance and profitability of hotels. They analyze data, manage online presence, optimize pricing strategies, and recommend operational changes to boost occupancy rates and revenue. Their expertise often includes revenue management, digital marketing, and process improvement, all conducted virtually. Many hotels hire remote specialists to gain expert insights without needing on-site staff.

What are the key skills and qualifications needed to thrive as a remote hotel optimization specialist?

To thrive as a Remote Hotel Optimization Specialist, you need expertise in revenue management, data analysis, and a solid understanding of hospitality operations, typically supported by experience in hotel management or a related field. Familiarity with property management systems (PMS), revenue management software, and channel management platforms is essential. Strong problem-solving abilities, analytical thinking, and effective communication skills help you interpret data and collaborate with hotel teams. These capabilities drive increased occupancy, maximize revenue, and ensure competitive positioning in the hospitality market.

What are some common challenges faced by professionals in remote hotel optimization, and how can they be effectively managed?

Professionals in remote hotel optimization often encounter challenges such as ensuring consistent communication with on-site staff, adapting rapidly to market changes, and leveraging data analytics across multiple properties. Effective management involves utilizing robust hotel management software, maintaining regular virtual meetings with property teams, and staying updated on industry trends. Building strong relationships with on-site personnel and developing clear processes for remote collaboration are also key to overcoming these challenges and driving revenue growth.

What is the difference between Remote Hotel Optimization vs Remote Revenue Manager?

AspectRemote Hotel OptimizationRemote Revenue Manager
Required CredentialsHospitality or hotel management experience, analytics skillsRevenue management certifications, analytics, and industry experience
Work EnvironmentRemote, hotel industry focus, data analysisRemote, focus on pricing strategies, revenue forecasting
Employer & Industry UsageHotels, hospitality companies, online booking platformsHotels, resorts, online travel agencies
Search & Comparison IntentOptimizing hotel performance remotelyMaximizing hotel revenue through pricing strategies

Remote Hotel Optimization focuses on improving overall hotel performance through data analysis and operational strategies, while Remote Revenue Manager specializes in pricing and revenue strategies to maximize income. Both roles are remote and industry-specific but differ in their core focus areas.

More about Remote Hotel Optimization jobs

What cities are hiring for Remote Hotel Optimization jobs?

Cities with the most Remote Hotel Optimization job openings:

What are the most commonly searched types of Hotel Optimization jobs?

The most popular types of Hotel Optimization jobs are:

What states have the most Remote Hotel Optimization jobs?

States with the most job openings for Remote Hotel Optimization jobs include:

Infographic showing various Remote Hotel Optimization job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 78% Physical, 5% Hybrid, and 17% Remote job distribution, with an average salary of $124,067 per year, or $59.6 per hour.

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago


Job description

Job Title: AI Engineer

Location: New York, NY

Department: Technology/Revenue Strategy

Reports To: Chief Executive Officer

FLSA Status: Exempt

Work Type: Remote Position with occasional travel to the Corporate Office

Employment Type: Full Time

Company: Rebel Hotel Company

About Rebel Hotel Company: Rebel Hotel Company is one of the fastest-growing third-party hotel management companies in the United States, recognized for delivering bold results, operational excellence, and distinctive guest experiences. We operate a diverse portfolio of full-service, lifestyle, and branded hotels across major metropolitan and resort markets. We are building a culture of leadership, innovation, and accountability—and we’re just getting started.

Position Summary: We're a hospitality company building the next generation of intelligent pricing, demand, and guest-experience systems. Today our commercial teams run rate strategy, RFP negotiations, and account planning on spreadsheets and intuition. We're hiring an AI Engineer to turn that work into software — models and tools that forecast demand, optimize rates, and surface account intelligence so our revenue managers make sharper decisions, faster.

This is a hands-on engineering role with direct line of sight to revenue. You'll work alongside revenue managers, sales leaders, and data analysts, shipping production systems that touch real pricing and booking decisions across our portfolio.

What You'll Build

  • Demand forecasting models that predict occupancy and room-night demand by property, segment, day-of-week, and season — accounting for events, seasonality, and booking pace.
  • Dynamic pricing and rate-optimization engines that recommend BAR and corporate rates, balancing occupancy, ADR, and RevPAR against competitor positioning.
  • Account intelligence tooling that ingests internal production data and external signals (M&A activity, headcount trends, travel-budget shifts) to flag growing accounts, at-risk accounts, and uncaptured market opportunity.
  • Labor and staffing models that forecast labor demand against projected occupancy and arrivals — optimizing schedules, hours, and cost across housekeeping, front desk, F&B, and other departments while protecting service levels.
  • RFP and negotiation support tools that help the team price contracts, model rate scenarios, and prioritize target accounts during RFP season.
  • LLM-powered workflows — summarizing market intelligence, drafting account strategy notes, and answering natural-language questions over revenue data.
  • A testing laboratory for beta technologies — stand up and run a controlled environment where new AI tools and models can be piloted, stress-tested, and validated against real operational data before broader rollout, including the experimentation framework, sandboxed data, and feedback loops with property and commercial teams

What You'll Do

  • Design, train, evaluate, and deploy machine learning models on real booking, rate, and market data.
  • Build data pipelines that bring together PMS, CRS, booking-channel, and third-party market data into clean, reliable feature sets.
  • Stand up the infrastructure to serve models in production — APIs, monitoring, retraining, and guardrails.
  • Operate the beta testing lab — design pilots, recruit internal users, measure results, and decide what graduates to production versus what gets killed.
  • Partner closely with revenue and commercial teams to translate domain knowledge into product, and to make sure outputs are trustworthy and actionable.
  • Define and track the metrics that matter — forecast accuracy, recommendation adoption, labor cost and productivity, and downstream revenue impact.

What We’re Looking For

Required

  • 3+ years building and shipping ML systems in production (not just notebooks).
  • Strong Python and the modern ML/data stack (e.g. pandas, scikit-learn, PyTorch or TensorFlow, SQL).
  • Solid grounding in forecasting, optimization, or recommendation/pricing problems.
  • Experience taking models from prototype to deployed service, including monitoring and iteration.
  • Ability to communicate clearly with non-technical stakeholders and translate business problems into technical ones.

Nice to have

  • Experience in hospitality, travel, airlines, retail, or another revenue-management-driven industry.
  • Familiarity with dynamic pricing, demand modeling, or yield/revenue management.
  • Experience integrating LLMs into applications (RAG, structured extraction, agentic workflows).
  • Cloud and MLOps experience (AWS/GCP/Azure, containerization, CI/CD for ML).
  • Comfort with experimentation and causal measurement (A/B testing, uplift modeling).

What We Offer:

  • Competitive base salary and performance-based incentive plan
  • Medical, dental, and vision insurance
  • 401(k) plan with company match
  • Paid time off and holidays
  • Career advancement opportunities within a rapidly growing company
  • A chance to be part of the Rebel movement redefining hospitality leadership

Why This Role

You'll own meaningful problems end-to-end, see your work move real revenue, and help build a data and AI capability from an early stage. If you want your models to ship and matter rather than sit in a backlog, this is that role.

Salary Range: $190,000 - $200,000 annually

At Rebel Hotel Company, we don’t manage hotels the old way—we challenge the status quo. If you’re ready to lead with vision, act with ownership, and make your mark in the hospitality world, we want to meet you.