Analytics Intern, Summer 2027

Jobtailor

Arizona

On-site

USD 25,000 - 39,000

Full time

4 days ago
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Job summary

Jobtailor in the United States is offering a data analytics internship based in Tempe, AZ and Dallas, TX. You will support analytics across Credit Risk, Pricing, Marketing, and other verticals, gaining hands-on experience with SQL, Python, Tableau, and Excel.

Work on-site Monday–Friday, 40 hours per week, with a graduation window between December 2027 and May 2028. The role focuses on data analysis, reporting, and delivering insights that drive customer experience and profitability.

Qualifications

  • Data analysis experience in a STEM field.
  • GPA of 3.5+ required.
  • Currently pursuing a quantitative degree.
  • Must be eligible for on-site internship in US.

Responsibilities

  • Analyze datasets to generate actionable insights.
  • Brainstorm data-driven solutions to analytics challenges.
  • Participate in all analytics lifecycle stages from design to deployment.
  • Support product improvements and customer insights initiatives.
  • Prepare timely findings reports for stakeholders.
  • Work on-site at Tempe, AZ and Dallas, TX.

Skills

Data analysis experience
Attention to detail
Verbal and written communication

Education

Bachelor's or Master's student (graduation Dec 2027 - May 2028)
GPA 3.5+

Tools

SQL
Python
Tableau
Excel

Job description

  • Support one of several analytics verticals: Credit Risk & Pricing Analytics, Loan Servicing Analytics, Marketing Analytics, Supply Chain Analytics, Retail Analytics, or SilverRock Analytics
  • Conduct data analysis to generate meaningful insights from datasets
  • Brainstorm ideas and provide creative solutions to data-analysis challenges
  • Participate in all phases of the analytics lifecycle, including research design, data collection, data processing, model building, deployment, and presentation of results
  • Innovate existing products and services using technologies and data analysis to identify opportunities to improve customer experience and profitability
  • Provide ad hoc analysis and support special projects as required
  • Prepare timely reports on findings
  • Work in the Tempe, Arizona and Dallas, Texas home offices on a regular on-site schedule
Requirements
  • Bachelor's or Master's student with a graduation date between December 2027 and May 2028
  • Pursuing a quantitative degree in Analytics, Data Science, Mathematics, Economics, Statistics, Physics, Computer Science, or another STEM field
  • GPA of 3.5 or higher
  • Data analysis experience
  • Working knowledge of SQL, Python, Tableau, and Excel
  • Strong analytics and reporting abilities
  • Excellent attention to detail
  • Problem-solving ability
  • Ability to thrive in a fast-paced environment
  • Intellectual curiosity
  • Excellent verbal and written communication skills
  • Successful completion of background and drug screening
  • Willingness to work on-site Monday-Friday, 40 hours per week
  • Relocation not provided for the internship
Core Competencies

Demonstrates strong data analysis capabilities with proficiency in SQL, Python, and Tableau, while effectively communicating insights and findings. Possesses a solid foundation in quantitative disciplines, ensuring attention to detail and problem-solving skills in a fast-paced environment.

Highest-signal resume keywords
  • Data Analysis Experience
  • SQL Proficiency
  • Python Proficiency
  • Tableau Knowledge
  • Strong Analytics and Reporting Abilities
Hard Skills
  • Data Analysis
  • SQL
  • Python
  • Tableau
  • Excel
  • Model Building
  • Data Processing
  • Research Design
  • Data Collection
  • Presentation of Results
Soft Skills
  • Attention to Detail
  • Problem-Solving Ability
  • Intellectual Curiosity
  • Excellent Verbal Communication
  • Excellent Written Communication
Industry Keywords
  • Analytics
  • Credit Risk
  • Pricing Analytics
  • Loan Servicing Analytics
  • Marketing Analytics
  • Supply Chain Analytics
  • Retail Analytics
  • Customer Experience
  • Profitability
  • Ad Hoc Analysis
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