Marketing & Ops Data Analyst

Accountabilities:

Manage reporting and analytics deliverables: Build, maintain, and improve datasets, reports, and performance metrics covering the full marketing and enrollment funnel, including advertising spend, cost per lead (CPL), cost per acquisition (CPA), leads, applications, and enrollments.
Develop actionable dashboards: Create and maintain interactive Power BI dashboards and recurring reports using data models and DAX, ensuring outputs are intuitive, well-documented, reliable, and useful for business stakeholders.
Optimize data models and pipelines: Write, maintain, and optimize SQL queries while contributing to data modeling and pipeline development in Databricks. Collaborate with senior team members to prepare clean, governed datasets for reporting and AI-driven analytics.
Analyze marketing and operational performance: Investigate changes in funnel performance, conversion rates, marketing channels, and customer cohorts to identify trends, understand underlying drivers, and recommend opportunities for improvement.
Support strategic financial and marketing analysis: Contribute to customer lifetime value (LTV) and return on advertising spend (ROAS) analyses, forecasting, experimentation, and Marketing Mix Modeling initiatives to improve marketing effectiveness and resource allocation.
Advance AI-enabled analytics: Help test, implement, and scale AI-powered analytical solutions, including automated reporting summaries, natural-language data queries, and intelligent reporting workflows. Share findings and successful approaches with the wider team.
Improve data quality and consistency: Validate and reconcile information across advertising platforms, customer relationship management (CRM) systems, and web analytics tools. Support tracking, tagging, and event-data validation while identifying and escalating discrepancies promptly.
Collaborate with cross-functional stakeholders: Partner with marketing, student success, and strategy teams to clarify business questions, prioritize requests, establish expectations, and deliver accurate insights within agreed timelines.
Promote self-service analytics and efficiency: Reduce reliance on manual reporting and one-off requests by developing scalable dashboards, improving documentation, and encouraging stakeholder adoption of analytical tools.
Maintain high standards of delivery: Take ownership of the accuracy, reliability, and timeliness of reporting while continuously expanding technical capabilities and independently managing increasingly complex analytical assignments.
Requirements:
Education: Bachelor's degree in economics, mathematics, statistics, finance, operations research, engineering, marketing, business, or a related field.
Professional experience: At least two years of experience in marketing analytics, business analytics, or a related analytical role.
SQL proficiency: Strong SQL skills, including querying, joining, and transforming data. Experience with common table expressions (CTEs) and window functions is an advantage.
Business intelligence and reporting: Hands-on experience building dashboards and reports using Power BI or a comparable business intelligence tool, with working knowledge of data modeling and DAX. Strong Microsoft Excel skills are also required.
Marketing analytics expertise: Experience analyzing marketing performance, conversion funnels, return on investment, and related business metrics, with the ability to independently conduct exploratory analyses and identify actionable insights.
Data storytelling and communication: Strong written and verbal communication skills, including the ability to translate complex analytical findings into clear, practical recommendations for nontechnical audiences.
Stakeholder management: A service-oriented mindset, strong relationship-building abilities, and the capacity to manage multiple requests, competing priorities, and tight deadlines in a fast-paced environment.
Analytical curiosity and adaptability: A proactive approach to problem-solving, comfort working through ambiguity, and enthusiasm for learning new analytical tools, technologies, and AI-enabled methods.
Preferred cloud data platform experience: Familiarity with Databricks, including Delta Lake, PySpark, and notebooks, or experience with other modern cloud data platforms.
Preferred programming skills: Experience using Python or R for data analysis, reporting automation, or workflow optimization.
Preferred AI analytics exposure: Familiarity with AI-powered reporting, automated insights, large language model (LLM)-based analytics, or natural-language data tools such as Databricks Genie.
Preferred marketing technology knowledge: Experience with web analytics platforms such as Google Analytics 4 (GA4) or Adobe Analytics, clickstream data, and CRM platforms.
Additional desirable experience: Exposure to paid media platforms such as Google Ads, Meta, or LinkedIn; marketing attribution; Marketing Mix Modeling; experimentation; customer research; survey design; or market analysis.
Benefits:
Remote work flexibility: Fully remote working arrangement within the United States.
Full-time employment: Opportunity to build a long-term career in marketing and operational analytics.
Professional development: Opportunities to deepen expertise in SQL, Power BI, Databricks, and modern data engineering practices.
Emerging technology exposure: Hands-on involvement in AI-enabled analytics and innovative approaches to reporting and business intelligence.
Cross-functional collaboration: Work closely with marketing, student success, and strategy teams to influence decisions and improve business outcomes.
Career growth: Opportunity to take ownership of increasingly complex analytics projects and expand technical and strategic responsibilities.
Meaningful impact: Contribute to data-driven decisions that support educational program growth, operational efficiency, and improved student outcomes.