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About This Role
The Senior Data Scientist is a dedicated role supporting IHG’s strategic partnership with Holiday Inn Club Vacations (HICV), responsible for leading the design, development, deployment, and ongoing operation of predictive and prescriptive AI/ML models.
Operating within a joint IHG–HICV delivery model, this role partners closely with business and technical stakeholders to deliver scalable, explainable, and production\-ready solutions. The role leverages an iterative, test\-and\-learn methodology to continuously enhance model performance and drive measurable business impact.
Your day to day
- Lead the end\-to\-end development and lifecycle management of predictive and prescriptive AI/ML models, from design through deployment and continuous optimization.
- Translate business objectives into scalable data science solutions, partnering with HICV stakeholders to improve key outcomes such as conversion, engagement, and activation.
- Design and execute experimentation frameworks (e.g., A/B and multivariate testing) to evaluate impact and optimize performance against defined KPIs.
- Operationalize models into production environments, enabling real\-time and batch scoring, and integrating outputs into key workflows (e.g., contact center routing, survey targeting, package activation).
- Ensure strong data governance, documentation, and model explainability, including clear definitions of inputs, features, methodologies, and outputs, while maintaining compliance with privacy and regulatory standards.
- Collaborate within a joint IHG–HICV governance model, contributing to steering committee reviews, prioritization, and ongoing performance monitoring and enhancement.
What we need from you
- Bachelor’s or Master’s degree in a quantitative field (e.g., mathematics, statistics, data science), or equivalent relevant experience
- 5–8 years of data science experience with demonstrated delivery of business impact
- Advanced proficiency in Python and SQL (including complex queries, stored procedures, and performance optimization)
- Strong experience with machine learning frameworks (e.g., scikit\-learn, XGBoost, TensorFlow, PyTorch; familiarity with LLM frameworks is a plus)
- Experience deploying models in cloud environments (e.g., GCP AI Platform/Vertex AI, AWS SageMaker)
- Expertise in causal inference, optimization techniques, and experimental design
- Experience with MLOps frameworks, including model deployment, monitoring, and lifecycle management
- Strong understanding of business impact modeling (e.g., ROI, LTV, incrementality)
- Solid grounding in statistical modeling (e.g., regression, time series, propensity modeling)
- Strong feature engineering and data preparation practices
- Strong problem\-solving skills and business acumen
- Ability to communicate complex analytical concepts to non\-technical stakeholders
- Attention to detail with a focus on governance and documentation
- Experience operating in cross\-company or client\-facing delivery models preferred
Location \- Our hybrid work structure is an expectation of three (3\) days a week in the Atlanta office. This expectation may be adjusted to evolve with the changing needs of the business.
The salary range for this role is $119,000\.00 to $155,000\.00\. This role is also eligible for bonus pay. We offer a comprehensive package of benefits including paid time off, medical/dental/vision insurance, 401K, and other benefits to employees.
At IHG Hotels \& Resorts, we work together to deliver True Hospitality for Good on a global scale. With corporate offices and over 6,000 hotel destinations worldwide, a career at IHG is the perfect way to broaden your horizons. You’ll experience our unique culture and brilliant colleagues who will support and inspire you. With a host of corporate opportunities to choose from, wherever you are on your career journey, and whatever you want to achieve there’s Room for You at IHG.
Over recent years, we’ve transformed our company. We have bold ambitions to drive performance and maintain our relentless focus on growth in order to be the hotel company of choice that guests \& owners love.
We are a hospitality business at our core and value connections and being together helps us foster a unique sense of belonging that also supports productivity. That’s why here at IHG, we give our colleagues flexibility and balance – working in a hybrid way, blending office and remote working collectively. We recognise that every role is different, that’s why leaders work with teams to determine how and when they collaborate.
We provide a wide range of benefits designed to help you live your best work life. These include impressive room discounts across our many properties, recharge days and volunteering days throughout the year. Through our myWellbeing framework, we are committed to supporting wellbeing in your health, lifestyle, and workplace. We offer a unique and inclusive culture, where there is always Room for You to belong, grow and make a difference.
Our mission is to welcome everyone and create inclusive teams where we celebrate difference and encourage colleagues to bring their whole selves to work. IHG Hotels \& Resorts provides equal employment opportunities to applicants and employees without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other category protected by applicable laws. We promote a culture of trust, support, and acceptance. Always welcoming different backgrounds, experiences, and perspectives.
Don't quite meet every single requirement, but still believe you'd be a great fit for the job? We'll never know unless you hit the 'Apply' button. Start your journey with us today.
Important information:
- The salary range listed is the lowest to highest pay scale we, in good faith, believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee’s pay position within the pay range will be based on several factors, including relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue\-based metrics, and business or organizational needs.
- No amount of pay is considered to be wages or compensation until it is earned, vested, and determinable. The amount and availability of any bonus, commission, or other form of compensation allocable to a particular employee remain in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.
- EEO Is The Law \- click here for more information about Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled/Sexual Orientation/Gender Identity.
- If you require reasonable accommodation during the application process, please click here.
- IHG does not accept applications, inquiries, or unsolicited CVs/resumes from staffing or recruiting agencies. Please click here for our agency policy.
- If you are a resident of or applying to a job opening in the State of Washington, please click here to read about applicable benefits.
Salary Context
This $119K-$155K range is below the median for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At IHG Hotels & Resorts, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($137K) sits 29% below the category median. Disclosed range: $119K to $155K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
IHG Hotels & Resorts AI Hiring
IHG Hotels & Resorts has 1 open AI role right now. They're hiring across Data Scientist. Based in Atlanta, GA, US. Compensation range: $155K - $155K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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