Revenue Intelligence Operations Analyst, Marketing

About the role

Data Analysis & Insights
- Analyze marketing performance data to identify trends, performance drivers, and optimization opportunities.
- Evaluate customer acquisition, engagement, and conversion metrics to support marketing decision-making.
- Design and implement scalable lead ingestion solutions using AI-driven data parsing, validation, enrichment, and automation techniques.
- Translate complex data into clear insights and recommendations for stakeholders.
- Support ad-hoc analysis and proactively identify opportunities for deeper insights.

Technical & Data Development
- Write efficient SQL queries to extract, transform, and analyze marketing and enterprise data.
- Use Python for data preparation, automation, and analysis.
- Assist with building and maintaining curated datasets, data models, and data quality checks.
- Utilize AI-assisted development tools, including Claude Code, to build interfaces, agents, and workflow automations.

Reporting & Collaboration
- Develop and maintain dashboards and marketing performance reports using BI tools.
- Automate recurring reporting processes to improve efficiency and scalability.
- Partner with marketing, analytics, data science and data engineering teams to support reporting and data needs.
- Document data definitions, logic, and reporting methodologies.

What you'll bring

• Technical Skills
  - Strong working knowledge of SQL, including joins, aggregations, and data transformations.
  - Basic to intermediate proficiency in Python with experience using data libraries (e.g., pandas, NumPy) through coursework, projects, or internships.
  - Exposure to Databricks, Apache Spark, or cloud-based data environments.
  - Experience working with real-world datasets and performing data validation and troubleshooting.
• Professional Skills
  - Strong curiosity and willingness to learn.
  - Strong analytical and problem-solving abilities with attention to detail.
  - Ability to communicate technical findings to non-technical audiences.
  - Ability to manage multiple priorities and collaborate effectively across teams.

Education & Experience

• Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field.
• Internship, academic project, or research experience involving data analysis is strongly preferred.

Nice to have

• Experience with Tableau, Power BI, or similar visualization tools
• Familiarity with marketing analytics concepts or campaign performance metrics
• Exposure to marketing platforms such as Google Analytics or Salesforce
• Experience using version control tools (e.g., Git)
• Understanding of ETL or data pipeline concepts