Data Scientist Intern, Summer 2027

Wing•Palo Alto, CA

1d•Hybrid

About The Position

Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. Wing is looking for a Data Scientist Intern to join our Business and Product Analytics & Data Science team based in Palo Alto, CA. You will work closely with cross-functional team members (e.g., Business Operations, Product) to turn complex business questions into clear, decision-focused data problems. In this role, you will use advanced analytics, modeling, and statistical analysis to evaluate tradeoffs, quantify impact, and guide strategic choices. You will perform in-depth analysis to answer important questions on business trends and proactively identify insights that enable cross-functional stakeholders to make confident, data-informed decisions.

Requirements

Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, or related field, graduating between December 2027 and August 2028
Strong coding proficiency in Python and SQL (familiarity with R or other data analysis libraries is highly beneficial).
Solid foundational knowledge of statistical methods including experimental design, hypothesis testing, regression modeling, and causal inference.
Familiarity with quantitative modeling, forecasting techniques, and data analytics.
Strong communication skills with the ability to explain mathematical or technical findings clearly to business partners.
High degree of curiosity with a strong desire to learn, collaborate, and tackle quantitative projects from raw data to structured insights.

Responsibilities

Execute deep-dive research and advanced analytics on complex datasets to uncover patterns, interpret trends, and assist in synthesizing product and business insights.
Support the development of predictive models to help forecast trends, measure operational trade-offs, and project business impact.
Conduct foundational statistical analysis and assist in the setup of experimental frameworks (e.g., A/B testing, causal inference) to help test hypotheses and evaluate ongoing performance.
Translate complex statistical outputs into clear, data-driven summaries and communicate analytical findings effectively to project team members.
Analyze key performance indicators (KPIs), identifying key trends, undertaking follow-up analysis to uncover valuable business patterns, and communicating these insights clearly to stakeholders.