Data & Automation Analyst
New
R
rater8Healthtech
United States - Remote; Employees must be physically located in the U.S., PST–ESTFull-TimeMiddle
Salary80,000 - 100,000 USD per year
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Job Details
- Experience
- 2 to 4 years
- Required Skills
- Project ManagementPythonSQLData Analysis
Requirements
- Bachelor’s degree in a quantitative field such as Computer Science, Data Analytics, Statistics, Business Administration, or Finance.
- 2 to 4 years of experience in a Business Analyst, Project Coordinator, or Data Analyst role.
- Proficiency in Python programming, including writing scripts, working with APIs, and building backend systems.
- Working knowledge of SQL for data extraction and manipulation.
- Systems thinking mindset with the ability to design workflows spanning multiple tools.
- Strong analytical and problem-solving skills with a focus on business impact.
- Ability to pressure-test data, findings, and AI-generated output with strong judgment.
- Clear written and verbal communication skills for collaborating with non-technical stakeholders.
- Experience with, or willingness to master, visual automation and integration platforms (e.g., Make.com, Zapier, n8n).
- Familiarity with marketing concepts like conversion funnels, A/B testing, and Calls-to-Action (CTAs).
- Proven track record of quick mastery in new technical concepts and systems.
Responsibilities
- Stress-test findings and perform analytical quality checks to ensure data-driven decisions are based on validated insights.
- Execute quantitative analysis of large datasets to identify market trends, customer behavior patterns, and competitive intelligence.
- Mine proprietary datasets to generate novel, defensible findings for case studies and thought leadership reports.
- Build and maintain data-driven outreach engines using AI-powered, personalized email workflows.
- Implement and maintain API integrations (GPT, Azure OpenAI) within marketing automation platforms.
- Design and map business processes and information flows to improve scalability and reduce inefficiency.
- Lead DataLabs projects from ideation through analytical testing and production deployment.
- Provide technical support, documentation, and training to enable other teams to build and own their automations.
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