Data Visualization Analyst

** Recruiters, please do not respond. This is W2 only **

Data Visualization Analyst

Onsite: Marysville, Ohio

Initial term: 12 months (position may run longer / transition to permanent)

Client: Fortune 100 Food & Beverage / Consumer Packaged Goods

Compensation: Competitive pay, benefits, 1.5x OT

The Data Visualization Analyst is responsible for transforming complex data sets into visual representations, such as charts, graphs, and interactive dashboards. They use various tools and software, such as Power BI, to create visually appealing and easily understandable data visualizations.

Primary Responsibilities:

• Dashboard Design and Development: Creating visually appealing and interactive dashboards using tools like Microsoft Power Platform or Excel to present data in a clear and concise manner.
• Data Analysis: Conducting in-depth analysis of complex data sets to identify trends, patterns, and insights.
• Data Visualization: Selecting appropriate charts, graphs and visual elements to effectively communicate data insights and key findings.
• Data Storytelling: Presenting data in a compelling and meaningful way to stakeholders, decisionmakers, or clients, using storytelling techniques to convey the significance of the data.
• Data Quality Assurance: Ensuring the accuracy, consistency and integrity of data used in visualizations, performing data validation and verification.
• Data Governance: Adhering to data governance policies and best practices, ensuring compliance with data privacy and security regulations.
• User Experience (UX) Design: Focusing on creating intuitive and user-friendly interfaces and dashboards that provide an optimal user experience, considering factors such as navigation, interactivity and accessibility.
• Collaboration: Working closely with scientists and engineers, data professionals, business intelligence teams, and general stakeholders (customers) to understand data requirements and objectives and collaborating with cross-functional teams to align visualizations with business goals.
• People Development: Developing and coaching others to gain proficiency in digital tools, data management and visualization.
• Communication and Presentation: Effectively communicating and presenting to both technical and non-technical audiences, explaining complex concepts in a clear and concise manner.
• Continuous Learning: Staying updated with the latest trends, tools and techniques in data visualization and data analytics to enhance skills and knowledge.

Additional Responsibilities:

• Training for Dashboard Owners and their teams
• Design, Generation, and Export of formatted reports from visualized data (e.g., in PDF)
• SharePoint Designer/Architect (for global / cross-site use)
• Preparation, Organization, and Launching of Content as Part of UX Design (e.g., Digital Spaces, etc.)
• Digital Tools Developer (using the Microsoft Power Platform or similar)
• Link with broader Digital Community within company and share best practices
• Experience in Advanced Analytics/Machine Learning is a plus
• Experience with programming languages such as Python and R is a plus

Job Qualifications (Minimum Education, Experience, and Knowledge)

• Education: Bachelor s degree in Data Science, Statistics, Mathematics, Computer Science or a related technical field. A Master s degree is a plus.
• Data Analysis Skills: Strong analytical skills are essential. Proficient in data manipulation, data cleaning and data analysis techniques to extract insights from complex datasets.
• Data Visualization Tools: Proficiency in data visualization tools such as Power Platform, QlikView and/or Excel is required. Demonstrated experience in creating interactive dashboards, designing visualizations and using advanced features of these tools is highly valued.
• Design and Visualization Principles: A strong understanding of design principles, color theory and information best practices is crucial for creating visually appealing and effective data visualizations.
• Visual Design: Knowledge of UX/UI design principles.
• Communication and Presentation Skills: Excellent communication skills, effectively communicating complex data insights to both technical and non-technical audiences. Presentation skills, storytelling abilities and the ability to explain data in a clear and concise manner.
• Attention to Detail: Have a keen eye for detail to ensure accuracy and quality in output. Ability to identify inconsistencies or errors in data and take necessary steps to rectify them.
• Problem Solving Abilities: Strong problem-solving skills. Ability to identify data related challenges, propose solutions and make data-driven recommendations.
• Continuous Learning: Willingness to learn and stay updated with the latest tools, techniques, and trends.
• Statistical Knowledge: Understand statistical concepts and techniques. Familiarity with statistical analysis methods and hypothesis testing.
• Programming Skills: Perform advanced data analysis, automate tasks and customize visualization. Knowledge of programming languages such as Python or R is a plus.