Data Analyst Intern, Risk & Fraud @ Super.com
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About Super.com
Super.com is dedicated to maximizing lives, both of our customers and employees, by offering opportunities to unlock potential and celebrate learning and impact. Join a fast-paced, high-growth tech company that cares about your career progression.
About The Role
As a Data Analyst Intern, Risk & Fraud for the Winter 2026 term, you will join our growing data team to answer strategic questions and support business strategy and rapid growth. You will use large datasets from various performance marketing channels to create data visualizations, build dashboards, run deep-dive analyses, and aid in decision-making.
- Data-driven Culture: Champion a culture that leverages data for strategy and decisions.
- Data Management: Access, clean, and organize raw data for team use.
- Visualizations: Create dashboards and funnels to communicate insights.
- Insightful Analysis: Run experiments and draw business conclusions from data.
About You
You are skilled in pulling, cleaning, and manipulating large datasets to develop stories for stakeholders. Proficiency in SQL, Python, and analytics tools like Looker, Amplitude, DBT, and Snowflake is essential. You possess a natural curiosity, an understanding of statistical methods, a capacity to work independently, and the drive to tie data insights to broader business goals.
What We Offer
- Top-of-market intern compensation package.
- Home office setup, weekly UberEats, term-based allowances for learning, development, and wellness.
- Opportunity to work with top talent from leading tech companies.
- A product used by millions with significant ownership and impact.
Key skills/competency
- Data Analysis
- SQL
- Python
- Risk Management
- Fraud Detection
- Data Visualization
- Dashboarding
- Statistical Methods
- Data Cleaning
- Analytics Tools
How to Get Hired at Super.com
🎯 Tips for Getting Hired
- Research Super.com's culture: Study their mission and impact on careers.
- Customize your resume: Emphasize SQL, Python, and analytics skills.
- Highlight internship projects: Showcase data management and visualization work.
- Prepare for technical questions: Practice data queries and statistical analysis.