What are the responsibilities and job description for the Data Operations Analyst position at MMGY Global?
At MMGY Global, we believe nothing shapes your view of the world like travel. So every day, we share our clients’ stories from a perspective that inspires people to see the world differently. Our personalized service and strategy connect media, consumers and influencers across the globe, taking people to new places and changing their views for the better. At MMGY, we inspire people to go places. The MMGY Travel Intelligence team fulfills that mission by designing, managing, and deploying research and analytics that transform how people explore and experience the world, making travel more accessible, sustainable, and enriching. Our vision is to build a global ecosystem of data, insight, and expertise that guides decision-making and empowers clients and agency partners to deliver meaningful, high-impact travel experiences worldwide. We have an immediate opening for a Data Operations Analyst to join our Washington DC area team in a hybrid function. This role is ideal for someone with a strong quantitative mindset, attention to detail, and a desire to grow in a data-driven organization. Duties & ResponsibilitiesThe Data Operations Analyst will support end-to-end survey and data workflows, including survey design, sample management, data processing, and final data delivery. This role also contributes to analytical modeling, quality control, and client reporting.
- Maintain, update, and execute data processing programs
- Manage survey workflows, including data cleaning, weighting, and consolidation
- Produce tabulated datasets for internal teams and external clients
- Assist in running and enhancing models to estimate visitation volume and travel spending
- Perform quality control checks to ensure data accuracy and integrity
- Conduct ad hoc analyses to support client and internal requests
- Collaborate with cross-functional teams on custom and syndicated research projects
- Identify opportunities to improve and streamline existing data processes
- Entry-level role designed for early-career candidates (0–1 year of experience); relevant experience may include internships, academic projects, or research
- Bachelor’s or Associate degree in statistics, data science, social sciences, or a related quantitative field, or equivalent coursework in statistics
- Proficiency in Python or R preferred
- Working knowledge of statistical software such as SPSS, SAS, or Stata preferred
- Basic proficiency in SQL
- Familiarity with survey methodology and survey data is a plus
- Exposure to machine learning or AI techniques is a plus
- Strong analytical thinking, problem-solving skills, and attention to detail
- Ability to manage multiple tasks and work collaboratively in a team environment