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Internship Snowflake Jobs in Florida (NOW HIRING)

Relevant internship, co-op, or graduate research may count toward experience. * Hands-on experience with SQL on a modern cloud data warehouse (Snowflake preferred) and with Python for analysis.

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Internship Snowflake information

What are the key skills and qualifications needed to thrive as an intern at Snowflake, and why are they important?

To thrive as an Intern at Snowflake, you generally need a solid foundation in computer science principles, programming skills (such as SQL, Python, or Java), and pursuit of a relevant degree like Computer Science or Engineering. Familiarity with cloud computing platforms, data warehousing concepts, and tools like Git and Snowflake’s own data platform is often expected. Strong problem-solving abilities, eagerness to learn, and effective communication set standout interns apart. These skills and qualities are crucial for contributing to innovative projects, collaborating with teams, and gaining the most from the hands-on learning experience.

What is an internship at Snowflake?

An Internship at Snowflake is a temporary position designed for students or recent graduates to gain hands-on experience in cloud data platform technologies. Interns work on real projects alongside experienced professionals, contributing to various teams such as engineering, product management, or sales. The internship provides valuable industry exposure, mentorship, and networking opportunities, often serving as a pathway to full-time employment.

What is the difference between Internship Snowflake vs Data Engineer Intern?

AspectInternship SnowflakeData Engineer Intern
Required CredentialsBasic SQL, Cloud platform familiaritySQL, programming skills, cloud knowledge
Work EnvironmentData warehousing, cloud-based platformsData pipelines, database management
Employer & Industry UsageTech companies, data-driven organizationsTech firms, analytics companies
Common Search & Comparison IntentUnderstanding Snowflake-specific rolesData infrastructure roles

Internship Snowflake focuses on roles involving Snowflake data warehousing technology, emphasizing cloud-based data storage and SQL skills. Data Engineer Interns typically work on building data pipelines, managing databases, and integrating various data sources. While both roles require SQL knowledge, Snowflake internships are more specialized in cloud data warehousing, whereas Data Engineer Internships cover broader data infrastructure tasks.

What types of projects do interns typically work on during a Snowflake internship?

During a Snowflake internship, interns are usually assigned to real-world projects that directly impact the company's products and services. These projects often involve collaborating with full-time engineers on tasks such as building new features, improving data pipeline efficiency, or contributing to open-source components. Interns are encouraged to participate in team meetings, code reviews, and brainstorming sessions, providing valuable learning opportunities and exposure to industry best practices. This hands-on experience helps interns develop technical skills and gain insight into the collaborative work environment at Snowflake.
What are the most commonly searched types of Snowflake jobs in Florida? The most popular types of Snowflake jobs in Florida are:
What are popular job titles related to Internship Snowflake jobs in Florida? For Internship Snowflake jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Internship Snowflake jobs in Florida look for? The top searched job categories for Internship Snowflake jobs in Florida are:
What cities in Florida are hiring for Internship Snowflake jobs? Cities in Florida with the most Internship Snowflake job openings:
Infographic showing various Internship Snowflake job openings in Florida as of August 2026, with employment types broken down into 8% Internship, 1% As Needed, 65% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

Data Scientist III- Operations

PODS Enterprises, LLC

Clearwater, FL • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


PODS rating

6.3

Company rating: 6.3 out of 10

Based on 29 frontline employees who took The Breakroom Quiz

11th of 29 rated removal and storage companies


Job description

JOB SUMMARY

As a Data Scientist on the Operations Data Science & AI team, you will report to the Director, Operations Data Science & AI and work with senior data scientists and operational stakeholders to develop optimization models, predictive models, and automated workflows. Your work will help PODS make better decisions across capacity planning, routing, scheduling, resource allocation, and other field operations.

ESSENTIAL DUTIES AND RESPONSIBILITIES

  • Develop optimization solutions:
    • Build and support optimization models for capacity planning, routing, scheduling, and resource allocation.
    • Formulate business problems using decision variables, objectives, and operational constraints.
    • Assist in root-cause analysis to surface optimization and automation opportunities across field operations.
  • Develop predictive models:
    • Build, test, and maintain forecasting, regression, classification, and anomaly-detection models for operational problems.
    • Prepare and validate data, engineer features, and evaluate model results.
  • Build and automate workflows:
    • Build reproducible data pipelines and automate recurring analyses, model runs, and reporting, replacing manual processes.
    • Contribute to shared tooling, frameworks, and standards so that solutions are repeatable.
  • Develop analytical assets and data models:
    • Maintain data models in Snowflake that other analysts and downstream tools rely on.
    • Create dashboards and decision-support tools that make results actionable.
  • Document and communicate clearly:
    • Document logic, methodology, and assumptions alongside every model, tool, or pipeline you build.
    • Present findings and their limitations in plain language to the team and operational stakeholders.

JOB QUALIFICATIONS: Essential Skills, Abilities and Example Behavior(s)

  • Mathematical optimization: Hands-on experience formulating and solving mixed-integer linear programming models, including defining decision variables, objectives, and constraints.
  • Optimization tools: Previous experience with Gurobi, Pyomo, OR-Tools, PuLP, CPLEX, or a similar optimization library or solver is required.
  • SQL and Python fluency: Strong SQL on a modern cloud data warehouse, preferably Snowflake, and Python for analysis and model development.
  • Applied machine learning: Experience building, testing, and validating forecasting, regression, classification, or other predictive models, with judgment about which method fits the problem.
  • Workflow automation: Experience building reproducible data pipelines and automating recurring analyses and model workflows.
  • Data visualization: Ability to communicate analytical and model outputs through clear visualizations and practical decision-support tools.
  • Communication and documentation: Ability to explain methods and results clearly and document work so that it is reproducible and reviewable.
  • Structure amid ambiguity: Ability to turn loosely defined operational problems into clear analytical questions and practical solutions.

JOB QUALIFICATIONS: Education & Experience Requirements

  • Bachelor’s degree in a quantitative field such as Data Science, Statistics, Operations Research, Industrial Engineering, Applied Mathematics, Physics, Computer Science, Engineering, Economics, or a related field required; master’s degree preferred
  • 5+ years of applied data science, machine learning, or quantitative analytics experience. Relevant internship, co-op, or graduate research may count toward experience.
  • Hands-on experience with SQL on a modern cloud data warehouse (Snowflake preferred) and with Python for analysis.
  • Experience or coursework in machine learning and mathematical optimization, with exposure to cloud-based data platforms such as Snowflake or AWS.
  • Experience supporting an Operations, Supply Chain, logistics, or other capacity-constrained business is a plus.

PHYSICAL REQUIREMENTS

  • Ability to sit at a desk and use a computer for up to 8 hours a day; Ability to use hands and fingers to type on a keyboard and use a mouse to navigate; Vision sufficient to view small details on a computer monitor
  • Ability to stand and walk up to 8 hours a day; ability to stoop, bend and lift boxes weighing up to 50 lbs.
  • Ability to hear and verbally communicate using a telephone handset and/or connected headset device

WORKING CONDITIONS

  • Regular business hours. Some additional hours may be required.
  • Travel requirements: Negligible
  • Climate-controlled office environment during normal business hours.
  • Regular attendance and punctuality required
  • May be subject to pre-employment criminal background check and/or drug screening as well as random drug screenings in accordance with company policy

What PODS employees say

Pay

Benefits

Hours and flexibility

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