Product Data Analyst Intern

RippleMatch, Inc.

Boston (MA)

Hybrid

USD 30,000 - 47,000

Full time

6 days ago
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Benefits offered by this job

Hybrid work model

Job summary

CarGurus is seeking a Product Data Analyst Intern for an 11-week Summer Internship. You will join the Product Data Analytics group, supporting product and engineering with analytics for user and dealer experiences, and you’ll dive into complex data to draw insightful conclusions.

The program runs June through August 2027, is full-time at 40 hours per week, and uses a hybrid model with about three days per week in our Boston office.

Qualifications

  • Pursuing analytics degree with data modeling and statistics.
  • Strong SQL familiarity; Python or R is a plus.
  • Foundational statistics knowledge (regression, significance testing, etc.).
  • Ability to create clear data visualizations.
  • Strong communication and stakeholder presentation skills.
  • Excellent organization and ability to break down unstructured problems.

Responsibilities

  • Embed within a Product domain and collaborate with a Product Data Analyst.
  • Perform exploratory data analysis to inform a business problem.
  • Translate sweeping requests into specific actionable insights.
  • Build dashboards and visual monitoring tools for daily decisions.
  • Present quantitative findings in clear terms to stakeholders.

Skills

SQL
Python/R
Statistics fundamentals
Data visualization
Communication skills
Problem solving

Education

Pursuing analytics degree

Tools

Snowflake
dbt
Claude Code
Omni

Job description

Role overview

CarGurus is looking for a Product Data Analyst Intern. Our Product Data Analytics organization as a whole supports our Product and Engineering teams, providing the final word on all analytics for CarGurus' user and dealer experiences. We are looking for thoughtful, curious, internally driven candidates who can dive into complex data and draw novel, insightful conclusions.

As a Product Data Analyst Intern, you will join an 11-week Summer Internship Program designed to give you hands-on experience, expand your professional network, and build core industry skills. This full-time opportunity (40 hours per week) runs from June through August 2027. CarGurus operates on a hybrid working model, and candidates should expect to work out of our Boston, MA office 60% of the time (approximately three days per week).

What you’ll do

  • Embed directly within a Product domain, working closely with a Product Data Analyst, and participating in team meetings, 1:1s, and other mentoring sessions.

  • Dive deep into our data and conduct exploratory data analysis to help inform a specific business problem.

  • Creatively compress sweeping requests into specific insights that address your stakeholders’ underlying needs.

  • Build intuitive dashboards and other visual monitoring tools to guide daily decision-making.

  • Communicate and present complex quantitative findings in easily digestible terms.

What you’ll bring

  • Currently pursuing a degree in an analytics or analytics-adjacent field, ideally involving complex data modeling, quantitative analysis, and applied statistics.

  • Strong familiarity with SQL. Experience with a programming language (Python, R, etc) is a plus.

  • Good foundational understanding of core statistical concepts (regression, significance testing, omitted variable bias, independence/dependence, etc.).

  • Knack for creative data visualizations.

  • Strong communication skills. Comfortable presenting an analysis with stakeholders beyond your core team.

  • Great organizational and task management skills. Able to take an unstructured problem and break it down into requisite pieces.

What you’ll learn

  • Hands-on experience with industry standard tools like: Snowflake, dbt, Claude Code, Omni, and more

  • Deep-dives into applied statistics in a real-world business environment using large data

  • How to scope projects, communicate findings, and work cross-functionally.

The displayed range represents the expected hourly rate for this position.

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