Data Analyst Intern (Summer 2027)
As a Data Analyst Intern at Lyft, you will play a crucial role in translating complex datasets into actionable business intelligence. You will support various teams by conducting deep-dive analyses on platform usage, market trends, and operational efficiency. Key responsibilities include building robust dashboards using tools like Tableau or Power BI, writing complex SQL queries to extract insights from vast databases, and presenting findings to product managers and executive stakeholders. This role offers a unique opportunity to apply statistical knowledge in a high-growth tech environment. Candidates should possess strong analytical skills, familiarity with data manipulation languages (SQL/Python), and a keen interest in the mobility sector. This internship is ideal for students looking to bridge academic theory with real-world application while contributing directly to Lyft's mission of connecting people.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
Preparing
1200
Question set
50
Duration
INTERNSHIP
Focus areas
People Also Ask (FAQs)
What is the last date to apply for Data Analyst Intern (Summer 2027)?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Data Analyst Intern (Summer 2027)?
Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.
Is there negative marking in the Lyft test?
The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.
What is the passing marks for this test?
The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.
How can I prepare for the Data Analyst Intern (Summer 2027) test?
Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: SQL, Python, Data Visualization, Statistics.
Quick start
Review the job summary, then jump into prep with the same flow used for exam starts.