Data Visualization Specialist (Part-Time)

Overview

This part-time opportunity is for a Data Visualization Specialist based in the United States and is managed by a partner company that handles the full application review and hiring process. The role blends analytics, product thinking, and business impact in a globally distributed, mission-focused setting.

You will turn complex data into clear, practical insights that help shape product direction and commercial choices. A major part of the job will involve building dashboards and analytical tools that enable leadership to understand user behavior, track product performance, and spot improvement opportunities. The position calls for both strong technical ability and the communication skills needed to present data in a clear, meaningful way.

In this role, your work will directly support decisions that improve digital services used across different markets and operating environments.

Responsibilities

• Create and maintain easy-to-use dashboards and visual reports that highlight key performance indicators, trends, and business metrics, including through tools such as Google Data Studio.
• Protect the quality of reporting by finding, investigating, and fixing data mismatches, pipeline errors, and other reliability issues.
• Work with product leadership to develop executive dashboards that inform roadmap priorities and commercial planning.
• Analyze product performance across regions to identify patterns, trends, and useful business insights.
• Run funnel and churn analyses to understand user journeys, locate friction points, and suggest ways to improve engagement and retention.
• Convert complex findings into clear, narrative-driven insights for senior stakeholders, partners, and internal teams.
• Help define product metrics and support a shared measurement approach across teams.

Requirements

• 3 to 5 years of experience in data analysis, data visualization, or a closely related analytical function.
• Strong SQL skills for querying and working with large datasets.
• Practical experience using dashboarding platforms such as Google Data Studio or similar tools.
• Advanced Excel knowledge for analysis, reporting, and data modeling tasks.
• Strong troubleshooting and problem-solving ability, with the capacity to explain technical issues in simple terms.
• Comfort working independently while also contributing effectively in remote, cross-functional, global teams.
• Experience with data warehouse tools such as BigQuery, Snowflake, or Redshift is an advantage.
• A degree in Computer Science, Data Science, Statistics, or a related discipline is preferred.
• Interest in using data to improve digital products and user outcomes in diverse or emerging markets.

Perks and Benefits

• Flexible part-time arrangement with an estimated 50% to 60% level of effort.
• Fully remote setup for candidates based in a global team environment.
• Chance to contribute to meaningful, large-scale digital services used across multiple countries.
• Opportunity to collaborate with international product and data teams.
• Exposure to strategic decision-making that affects product growth and user experience.
• Competitive pay aligned with experience and the scope of work.

Additional Information

This role is posted on behalf of a partner company, which is responsible for reviewing applications and managing the next stages of the hiring process. Selection is handled through an AI-assisted matching workflow that helps identify candidates who best match the core requirements before sharing a shortlist with the employer. Final hiring decisions, interviews, and assessments are managed by the employer’s internal team.

By applying, candidates acknowledge that personal data may be processed to evaluate candidacy and shared with the hiring employer under applicable data protection principles, including legitimate interest and pre-contractual measures where relevant. Applicants may request access, correction, deletion, or objection regarding their data at any time. AI tools may be used to assist with reviewing applications and identifying inconsistencies, but human judgment remains central to the final decision.