Marketing & Ops Data Analyst

New

JobgetherEducation analytics

Based in the United StatesFull-TimeJunior

Salary not disclosed

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Job Details

Experience: At least two years of experience in marketing analytics, business analytics, or a related analytical role.
Required Skills: PythonSQLMicrosoft Power BIMicrosoft ExcelData modelingDatabricksR

Bachelor's degree in economics, mathematics, statistics, finance, operations research, engineering, marketing, business, or a related field.
At least two years of experience in marketing analytics, business analytics, or a related analytical role.
Strong SQL skills, including querying, joining, and transforming data.
Hands-on experience building dashboards and reports using Power BI or a comparable business intelligence tool.
Working knowledge of data modeling and DAX.
Strong Microsoft Excel skills.
Experience analyzing marketing performance, conversion funnels, return on investment, and related business metrics.
Ability to conduct exploratory analyses and identify actionable insights.
Strong written and verbal communication skills, including translating analytical findings into practical recommendations for nontechnical audiences.
Ability to manage multiple requests, competing priorities, and tight deadlines.
Familiarity with Databricks, Delta Lake, PySpark, and notebooks, or other modern cloud data platforms, is preferred.
Python or R experience, AI-powered reporting exposure, and knowledge of web analytics, CRM, or paid media platforms are preferred.

Build, maintain, and improve datasets, reports, and performance metrics across the marketing and enrollment funnel.
Create and maintain interactive Power BI dashboards and recurring reports using data models and DAX.
Write, maintain, and optimize SQL queries and contribute to data modeling and pipeline development in Databricks.
Analyze funnel performance, conversion rates, marketing channels, and customer cohorts to identify trends and recommend improvements.
Contribute to customer lifetime value and return on advertising spend analyses, forecasting, experimentation, and Marketing Mix Modeling initiatives.
Help test, implement, and scale AI-powered analytics, including automated reporting summaries, natural-language data queries, and intelligent reporting workflows.
Validate and reconcile data across advertising platforms, CRM systems, and web analytics tools; support tracking, tagging, and event-data validation.
Collaborate with marketing, student success, and strategy teams to clarify questions, prioritize requests, and deliver insights.
Develop scalable dashboards and improve documentation to support self-service analytics and reduce manual reporting.
Ensure reporting accuracy, reliability, and timeliness while taking on increasingly complex analytical assignments.

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