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Travel Data Analytics Jobs (NOW HIRING)

HD Supply

Manager, Data Analytics

Atlanta, GA

... data. * Provides support to multiple departments to ensure that business intelligence, analytics ... Typically requires overnight travel 20% to 50% of the time. Education and Experience * Typically ...

New

Artemis Arc

Project Manager - Data Analytics Lead

The Data Analytics Lead works closely with Government leadership, operational teams, and ... However, travel for occasional in-person meetings will be required. Minimum Qualifications * 10 ...

Highspring

Senior Consultant - Data & Analytics

Mclean, VA · On-site

$76K - $122K/yr

Flexibility for travel, as needed Preferably, You Will Have: * Experience designing data architectures and analytics solutions in cloud-native environments * Familiarity with modern data engineering ...

Artemis Arc

The Data Analytics Lead works closely with Government leadership, operational teams, and ... However, travel for occasional in-person meetings will be required. Minimum Qualifications * 10 ...

KEEN Footwear

Sr. Director, Data & Analytics

Portland, OR · On-site

$217K - $229K/yr

It defines how data and analytics create competitive advantage across merchandising, DTC, wholesale ... Travel Required: Yes, 5% of the time. Base Salary: $217,600.00 - $229,615.00 The salary range ...

Hylant

Lead Data & Analytics Architect

Toledo, OH · On-site

Translate business and analytical requirements into scalable, secure, and feasible data ... Must be willing and able to travel for in-person meetings at least on a quarterly basis * Ability ...

Hylant

Lead Data & Analytics Architect

Detroit, MI

Translate business and analytical requirements into scalable, secure, and feasible data ... Must be willing and able to travel for in-person meetings at least on a quarterly basis * Ability ...

Hylant

Lead Data & Analytics Architect

Toledo, OH · On-site

They are seeking a Lead Data & Analytics Architect to define and evolve the enterprise application ... and able to travel for in-person meetings at least on a quarterly basis. • Ability and ...

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Travel Data Analytics information

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How much do travel data analytics jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for travel data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Travel Data Analytics is a field that values skills and experience over age; many professionals transition into data science at 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and tools like SQL or Python, and building a strong portfolio or certifications. Age should not be a barrier if you actively develop your expertise and stay current with industry trends.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but the role of a data analyst involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Data analysts will increasingly work alongside AI tools, focusing on tasks that require critical thinking, domain expertise, and communication skills.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Director or Chief Data Officer typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in machine learning, statistical analysis, and leadership, and they oversee large data teams and strategic initiatives.

What is travel data analytics?

Travel data analytics refers to the process of collecting, processing, and analyzing data related to the travel industry, such as flight bookings, hotel reservations, customer preferences, and travel trends. Professionals in this field use statistical and analytical methods to uncover insights that can help travel companies optimize operations, improve customer experiences, and increase profitability. By leveraging large datasets, they can identify emerging patterns, forecast demand, and make data-driven decisions to stay competitive in the market.

What is the difference between Travel Data Analytics vs Travel Data Analyst?

AspectTravel Data AnalyticsTravel Data Analyst
Required CredentialsBachelor's degree in Data Science, Analytics, or related field; proficiency in data toolsBachelor's degree in related field; basic data analysis skills
Work EnvironmentData teams, travel companies, analytics departmentsTravel agencies, tour operators, hospitality firms
Employer & Industry UsageUsed for strategic insights, forecasting, and decision-makingUsed for reporting, data interpretation, and operational support

Travel Data Analytics involves analyzing large datasets to generate strategic insights, often requiring advanced skills and tools. In contrast, a Travel Data Analyst focuses on interpreting data for operational purposes, typically with less emphasis on complex analytics. Both roles are essential in the travel industry but differ in scope and technical depth.

What is a travel data analyst?

A travel data analyst is a professional who collects, analyzes, and interprets data related to travel patterns, customer behavior, and industry trends. They use tools like Excel, SQL, and data visualization software to support decision-making and improve travel services or marketing strategies.

What are the key skills and qualifications needed to thrive as a Travel Data Analyst, and why are they important?

To thrive as a Travel Data Analyst, you need strong analytical abilities, proficiency in statistics, and a background in data analysis or a related field. Familiarity with data visualization tools like Tableau or Power BI, SQL databases, and potentially certifications in analytics or data science are typical requirements. Excellent problem-solving, communication, and attention to detail help you interpret trends and present actionable insights to stakeholders. These skills are crucial for optimizing travel operations, enhancing customer experiences, and driving data-informed decisions in the travel industry.

What are some common challenges faced in a Travel Data Analytics role, and how can they be addressed?

Professionals in Travel Data Analytics often encounter challenges such as integrating data from multiple sources (e.g., booking engines, customer reviews, and global distribution systems) and ensuring data quality and consistency. Addressing these challenges requires strong data management skills, familiarity with ETL (Extract, Transform, Load) processes, and effective communication with IT and business teams to clarify requirements. Staying updated with industry-specific analytics tools and trends also helps in transforming complex datasets into actionable insights for travel businesses.
More about Travel Data Analytics jobs
What cities are hiring for Travel Data Analytics jobs? Cities with the most Travel Data Analytics job openings:
What states have the most Travel Data Analytics jobs? States with the most job openings for Travel Data Analytics jobs include:
What job categories do people searching Travel Data Analytics jobs look for? The top searched job categories for Travel Data Analytics jobs are:
Travel Data Analytics jobs near you
Infographic showing various Travel Data Analytics job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.

Manager, Data & Analytics

Highspring (Formerly MorganFranklin Consulting)

Mclean, VA • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Highspring is a consulting firm that focuses on delivering data and analytics solutions to Fortune 100 brands and mid-market firms. The Manager, Data & Analytics will lead projects to design and build data warehouses, develop data pipelines, and implement analytics solutions, while collaborating with clients to address their data challenges and business objectives.
Responsibilities:
• Design and build modern data warehouses and analytics-ready data models.
• Develop scalable, reliable data pipelines using cloud-based data platforms.
• Implement analytics, reporting, and visualization solutions that translate complex data into clear, actionable insights for client stakeholders.
• Partner with client teams to understand business objectives, data challenges, and success metrics through interviews and working sessions.
• Manage discrete project workstreams, balancing technical execution with client communication and delivery timelines.
• Present findings, recommendations, and solution designs to both technical and non-technical audiences.
• Leverage AI-assisted development environments to design, generate, test, and iterate on production-quality analytics and data engineering code.
• Support broader data transformation initiatives, including system implementations, migrations, and modernization efforts.
• Actively participate in internal knowledge sharing, mentoring, and career development activities.
• Support the shaping of the strategic direction of our growing AI/ML, automation, and Data Analytics practice.
• Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping.
• Support data transformation initiatives across a range of service lines, including: M&A Lifecycle (integrations, divestitures, and carveouts), Finance Transformation, Enterprise Data Strategy / Governance Standup, Process Improvement and Automation, System Implementations / Migrations, Data and Automation Strategy and Road mapping (including how companies can leverage AI, ML, and other advanced data modeling concepts).
• Identify insights through use of statistical, algorithmic, mining and visualization techniques.
• Conduct interviews with client stakeholders to identify process and data challenges.
• Document and present findings to both technical and non-technical audiences.
• Develop analytical proof-of-concept prototypes and/ or deliver large-scale analytical platform implementations to fulfill clients’ tactical and strategic requirements.
• Develop business procedures and data management policies for ensuring data accuracy and control.
• Create model documentation, develop implementation roadmaps, and perform knowledge transfers.
Qualifications:
Required:
• 4+ years of data analytics, AI, ML, or GenAI experience
• Tier 1/Tier 2 consulting or professional services firms.
• Experience architecting and developing AI/ML solutions.
• Experience programming in Python, SQL, and/or R.
• Experience using GitHub (e.g., source code management).
• Comprehensive knowledge of modern statistical learning methods.
• Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets.
• Experience with any of the following commercial analytics, automation, and AI/ML tools: Alteryx, Power BI, Tableau, Power Automate, UiPath, Automation Anywhere, AI/ML/GenAI platforms, Informatica, Oracle EDMC, etc.
• Proven ability to lead, motivate and build teams that deliver services and solutions that surpass client expectations.
• Ability to lead workshops, including the gathering/documenting of requirements and use-cases and recommendation of envisioned processes.
• Experience presenting to CXO suite.
• Industry experience within Financial Services, Technology/SaaS, and/or Supply Chain.
• Understanding of typical software development lifecycles (Waterfall and Agile) and their associated lifecycle artifacts.
• Experience with identifying and correcting problems in imperfect data and processes.
• Bachelor's degree in Mathematics, Statistics, Computer Science, Information Systems, or other technology-related field or equivalent number of years of experience
• Flexibility to accommodate travel up to 25%.
Preferred:
• Strong business skills and experience in accounting, corporate finance, and FP&A.
• Familiarity with the M&A transaction lifecycle.
• Master’s degree in Information Technology, Statistics, Physics, Analytics or related field.
• Experience managing technical development by acting as a liaison between the technical team and the user community.
Company:
MorganFranklin Consulting is now Highspring, a leading global professional services organization with three integrated offerings—Consulting, Managed Services, and Talent Solutions. Founded in 1998, the company is headquartered in Mclean, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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