Ecosystem Strategic Finance Data Analyst

Ecosystem Strategic Finance Data Analyst 16192

• Hourly pay: $40-$55/hr (Pay varies based on the candidate's experience and location)
• Worksite: Leading professional development and networking company (Remote, Candidates must be located in the United States)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program
• 40 hours/week, 6 Month Assignment

A leading professional networking company seeks an Ecosystem Strategic Finance Data Analyst. The successful candidate will lead data-driven recommendations and insights to support strategic projects across the ecosystem's strategic finance. The company offers a great work environment!

Ecosystem Strategic Finance Data Analyst Responsibilities:

• Understand the business, track operational performance, and provide insights and recommendations.
• Support company-wide programs through ownership of analytical projects.
• Build dashboards and automated reports, working proficiently with data visualization and querying/analysis tools (e.g., Tableau, SQL, Python).
• Own data tables and work with stakeholders to ensure available data is accurate, consistent, and timely.

Ecosystem Strategic Finance Data Analyst Qualifications:

• 2+ years of experience working with data in a business setting, including data management, process execution, operations, reporting, or analytics.
• BS degree in a quantitative discipline.
• Ability to leverage numbers and insights to influence & drive sound decision-making is preferred.
• Ability to build strong partnerships and collaborate with stakeholders is preferred.
• Experience in communicating effectively and presenting to Senior Executives is preferred.
• Experience with manipulating massive-scale structured and unstructured data is preferred.
• Experience creating and maintaining business-critical data warehouse tables using SQL is preferred.
• Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.) is preferred.
• Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript) is preferred.

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