Associate Data Analyst (Project Hire/Internal Assignment)

The Walt Disney Company•Lake Buena Vista, FL

2d•Onsite

About The Position

The Associate Data Analyst is a key member of the team responsible for transforming complex data from our computer vision platforms into tangible operational improvements. The Data Platforms team designs and assists in deploying computer vision models to enhance safety and efficiency across Disney’s Parks worldwide. We are looking for a detail-oriented analyst eager to learn our pipelines and data flows, contribute to analysis and reporting, and help drive data-informed decisions across a globally deployed platform. This role is about more than running reports: it is about developing an understanding of the “why” behind the data. You will help identify trends, review detection outputs, and learn to analyze where the system is succeeding and where it is missing the mark (false positives and false negatives). You will support the bridge between the technical architecture and the project team, helping translate complex metrics into clear, actionable intelligence that improves the experience for both Guests and Cast Members. You will also assist engineering and program leadership on timelines, documentation, and communications. This is an estimated 15-month Project Hire position with no guarantee of permanent placement.

Requirements

1+ years of experience in data analysis, project analysis, or a technical analytical role.
Working knowledge of data generated by computer vision or machine learning models, including familiarity with how detection outputs are evaluated and interpreted.
Familiarity working in a Linux environment, including a working understanding of containers (Docker); exposure to orchestration tools such as Kubernetes (K8s) is a plus.
Ability to look at a set of data and begin to identify patterns or trends, with a desire to develop deeper analytical skills over time.
Familiarity with data tools for visualization and analysis (e.g., Tableau, Power BI, SQL, Python or R); willingness to learn tools used by the team.
Expert in Excel, including VLOOKUPs, pivot tables, charts, and complex formulas, with strong SQL skills for working with large datasets.
Ability to independently analyze data and translate insights into clear, actionable recommendations.
Proven ability to create clear, visually compelling presentations and tailor messaging for global audiences, including navigating language barriers and working with diverse, cross-functional stakeholders.
Experience presenting complex findings to a range of audiences, including technical teams, operations leaders, and internal and external executives—effectively simplifying content for non-technical stakeholders.
Good written and verbal communication skills and a willingness to engage with both technical and non-technical teammates.
Ability to manage your own time and priorities, staying organized when working across multiple tasks or stakeholders.
A high level of attention to detail—especially when dealing with data that drives critical operational decisions.
Flexibility to travel occasionally to domestic and international partner locations (including APAC and EMEA) to support stakeholder alignment and business initiatives

Nice To Haves

Academic or project-based exposure to computer vision or machine learning concepts (e.g., coursework, capstone projects, or personal projects)
Experience with VBA & Macros in Excel is a plus
Curiosity about predictive analytics or an interest in understanding the difference between lead indicators (metrics that predict an event) and lag indicators (metrics that report what already happened)

Responsibilities

Pull, organize, and review data from computer vision platforms to help the team identify patterns in detection behavior and flag emerging trends for review
Run structured reviews of detection outputs, log instances of false positives and false negatives, and compile findings into reports that help technical teams understand where tuning is needed
Perform routine checks on data pipeline health, flag anomalies or gaps in data flow, and escalate issues to senior team members for resolution
Carry out defined support tasks for container-based applications in Linux environments, follow documented procedures for routine maintenance, and escalate issues to software engineers when needed
Summarize analytical findings in clear, structured formats that make it easy for senior team members to draw conclusions and present to leadership
Monitor recurring data patterns over time and document observations that may indicate early warning signs, supporting the team’s efforts to move from reactive to proactive operations
Keep existing dashboards and performance briefings up to date with current data, flagging anything that looks off to senior team members before it goes to leadership
Participate in working sessions with operations staff, data scientists, and engineers, taking clear notes and following up on action items to keep projects moving
Maintain accurate records, trackers, and status updates that support the team’s project management needs as the program scales to additional sites
When trends or anomalies are flagged, gather relevant data, document what was observed, and support senior analysts in working through the root cause investigation
After a tuning update or process change is made, run before-and-after comparisons using defined metrics and document whether outcomes improved
Handle sensitive operational and Guest information with a high level of discretion and accuracy