Snowflake, a pioneering data platform built for the cloud, offers a unique opportunity for recent college graduates to join its team as Data Science Interns. This role involves applying machine learning to a variety of domain-specific use-cases across Snowflake’s departments, including Legal, Sales, IT, Security, and more. As a generalist role, it provides a chance to tackle a wide range of problems using diverse models and methods.
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What Snowflake Offers:
- Paid, Full-Time Internships: Immerse yourself in the software industry.
- Post-Internship Opportunities: Potential for return internships or full-time roles.
- Inclusive Culture: Experience a fast-paced, fun, and inclusive work environment.
- Expert Collaboration: Work with world-class experts on challenging projects.
- Real Contributions: Make meaningful contributions to systems used by customers.
- High Access to Supervisors: Receive detailed direction and feedback throughout the internship.
- Team Inclusion: Be treated as a full member of the Snowflake team, with access to company meetings, flexible hours, and more.
- Perks: Enjoy swag, casual dress code, and accommodations for remote work. When in office, benefit from catered lunches, gaming consoles, happy hours, and company outings.
Expectations from Candidates:
- Enrollment: Must be actively enrolled in an accredited college/university program.
- Educational Background: Completed undergraduate degree and currently enrolled in a Master’s or PhD program in a quantitative discipline.
- Skills: Proficiency in Python (including popular ML packages) and SQL, knowledge of probability & statistics, machine learning, data science, and data structures & algorithms.
- Research Interests: Interests in statistical learning, causal inference, optimization theory, machine learning, or related areas.
- Critical Thinking: Strong analytical skills and eagerness to learn.
- Communication: Good communication skills are essential.
Learning Opportunities:
- Data Analysis: Analyze real-world, large-scale, noisy data sets.
- ML Problem Formulation: Develop algorithmic solutions for ML problems.
- Data Tech Tools: Work with typical tools in a data tech stack.
- ML Pipelines: Develop and manage ML pipelines.
- Model Lifecycle Management: Understand the lifecycle of different ML methods.
- Scaling ML Methods: Learn how to apply ML methods at scale.
Accomplishments in This Role:
- Collaboration: Work with a high-performing team of data scientists and analysts.
- Research: Generalize data science and machine learning solutions.
- Business Opportunities: Identify and develop algorithms for business opportunities within Snowflake.
- Technical Advances: Drive advances in forecasting, anomaly detection, user behavior modeling, churn analysis, and recommendation engines.
- Creative Thinking: Think proactively to contribute to Snowflake’s data science roadmap.
- Customer Zero Initiatives: Drive Snowflake on Snowflake projects.
Interview Process:
- Online Assessment (OA):
- Duration: 150 minutes.
- Content: Kaggle machine learning question involving hotel prediction. Multiple submissions are encouraged due to the lengthy training times for some ML models. Practice Kaggle questions beforehand to get familiar with the format.
- Questions: Two coding questions (one ML and one algorithm) similar to LeetCode.
- Technical Interview:
- Duration: 200 minutes.
- Content: Two questions—one SQL and one data science-related. The SQL question is medium-level, while the data science question is more time-consuming.
- Setup: Build a model on Jupyter Notebook. Candidates will receive a coding challenge via Hackerrank, involving a complex ML project to be completed within 4 hours.
- Interview Rounds:
- Introduction: Discuss your projects, tech stack familiarity, and challenges tackled.
- SQL Theory and Practical Questions: Topics include database vs. data warehouse, constraints, primary key, candidate key, super key, joins, and practical queries.
- Coding Challenges: Examples include finding the 3rd highest salary, identifying the department with the most active projects, and listing employee names with their departments for specific projects.
- Comparison: Brief comparison of Java and Python.
Compensation and Benefits:
- Base Salary: Estimated average base salary is $108,581, with recent data suggesting $108,663.
- Additional Compensation: Eligible for Snowflake’s bonus and equity plan.
- Benefits Package: Includes medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
Snowflake is scaling rapidly, seeking individuals who share its values, challenge conventional thinking, and push the pace of innovation. Ready to make an impact? Apply here.
Introducing Myself:
- Projects and Challenges: Share details about your projects and the challenges you faced.
- Tech Stacks: Discuss your familiarity with various tech stacks.
- OOP Questions: Be prepared to answer basic Object-Oriented Programming questions.
Detailed Technical Interview:
- SQL Questions: In-depth SQL theory and practical questions.
- Algorithm Challenges: Engage with complex algorithmic problems.
- Technical Comparison: Briefly compare different programming languages like Java and Python.
Embark on a journey with Snowflake to build the future of data and unlock endless insights to tackle today’s challenges and reveal tomorrow’s possibilities.