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Data Analyst

Remote (US Timezone)Full-timeData

At SwiftPrep, we believe preparing for interviews shouldn't feel like shooting in the dark. We're building an AI-powered platform that scrapes multiple interview sources (Glassdoor, Reddit, Blind, Fishbowl, and more) and uses LLM scoring to generate personalized prep plans, contact discovery for networking, and comprehensive cheatsheets — giving candidates the confidence and focus they need to succeed. Join us as a Data Analyst to transform raw user behavior data, interview intelligence, and platform metrics into actionable insights that drive our AI recommendations and product improvements. You'll work directly with the datasets powering our contact discovery, prep plan generation, and interview profile scoring — directly impacting how millions of users prepare for their careers.

Responsibilities

  • Analyze user interaction patterns across prep plans, contact discovery, and interview profiles to optimize AI recommendations
  • Measure and improve LLM scoring accuracy for interview intelligence from multiple sources (Glassdoor, Reddit, Blind, etc.)
  • Track contact discovery success rates and confidence score performance to enhance networking outcomes
  • Build dashboards showing prep plan effectiveness, user engagement metrics, and feature adoption rates
  • Collaborate with product and AI teams to validate data-driven improvements to interview scoring algorithms
  • Monitor data quality and accuracy for job posting extraction, company research, and role-specific content
  • Identify trends in interview questions, company preferences, and preparation patterns across industries
  • Develop predictive models for user success rates and feature recommendations

Requirements

  • 2-4 years of experience in data analysis or business intelligence
  • Proficiency in SQL and experience with modern data warehouses (Snowflake, BigQuery, or Redshift)
  • Strong skills in Excel/Google Sheets and data visualization tools (Tableau, Looker, or similar)
  • Experience with Python for data manipulation, pandas, and basic statistical analysis
  • Familiarity with AI/ML concepts and ability to analyze model performance metrics
  • Experience analyzing SaaS product metrics and user engagement patterns
  • Ability to translate complex data insights into clear, actionable recommendations for product teams
  • Comfort working with unstructured data and building insights from ambiguous datasets