Internship Program, Business Intelligence

Red Bull•Santa Monica, CA

About The Position

Candidates are encouraged to apply to 2 or fewer internship roles during a given internship recruiting cycle. Are you excited by the idea of turning complex data into clear, actionable insights that improve how a business operates in the real world? As an intern on the Distribution Services Business Intelligence team, you will support impactful projects that deepen our understanding of sales feedback and data infrastructure. You’ll explore text-based feedback using Large Language Models (LLM), connect key sales metrics, and help optimize our Snowflake data environment. In doing so, you’ll build core skills in SQL, Python, and analytics while collaborating with stakeholders across Sales, Operations, & Talent.

Requirements

Actively enrolled in college/university as an undergraduate or graduate student
Available to work full-time (40 hours per week) for the duration of the internship
Demonstrated initiative through academics, work experience, or extracurricular involvement
Comfortable writing python code
Familiarity with SQL
A growth mindset, with the ability to learn quickly, adapt to new environments, and incorporate feedback

Nice To Haves

experience in LLM is a plus

Responsibilities

SENTIMENT ANALYSIS & TEXT PARSING Examine managers’ free-text in-store assessments from around the country using Python & LLM packages. Determine a sentiment analysis of manager responses. Evaluate response quality by assessing the impact of length, keywords, and grouping similar assessments using different synonyms. Determine the impact of the highest-quality responses in their respective markets.
COMPARATIVE ANALYSIS Inspect historical sequential datasets and help find the tangible numeric impact between each dataset on a granular store level. Connect Offtake, Depletions, & Backstock to build a full picture of the sales path of a can of Red Bull. Uncover potential causal factors between datasets, measuring the relationship & impact each individual metric has.
DATA TABLE VALIDATION (SNOWFLAKE) Support data tables review, ensuring that large-scale tables from related / different sources match each other; Data table sizes ranging from 10k – 300M rows. Learn to establish automated system monitors, warning of data issues as soon as they occur. Apply theoretical data structures to practical issues, synchronizing large datasets used for everyday business.