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Data Science Intern - Summer 2025

We are currently seeking a Data Science Intern to join our team for a hands-on internship focused on time series modeling and forecasting. This internship offers an opportunity to contribute directly to prototyping and implementing real-time analytics solutions for operational and customer-facing applications.

PlanetArt internships are full-time positions, and interns should expect to work Monday through Friday, up to 40 hours per week, typically between 9am–5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have scheduling conflicts such as classes or other employment during the PlanetArt workday.

By applying to this position, your application will be considered for the Data Science Intern role located in Calabasas, California.

Key job responsibilities

  • Prototype and evaluate time series forecasting and anomaly detection models.
  • Perform exploratory data analysis on seasonality, trends, and signal quality to determine the best modeling approach.
  • Develop model pipelines for deployment and simulation using Python (e.g., StatsModels, Scikit-learn, NumPy, Pandas, XGBoost, PyTorch).
  • Support data ingestion and preprocessing pipelines for time series datasets using Spark and SQL.
  • Participate in building validation workflows to assess forecast accuracy and anomaly detection precision using statistical benchmarks.
  • Collaborate cross-functionally with analysts, engineers, and business stakeholders to translate forecasting results into actionable insights.
  • Contribute to the visualization of model results, uncertainty intervals, and anomaly flags using Jupyter, Streamlit, Tableau, or web-based dashboards.
  • Stay updated on academic and industry advances in time series modeling, changepoint detection, traditional ML, and Deep Learning forecasting.

Qualifications:

  • Currently enrolled in a Bachelor’s or Master’s program in Data Science, Statistics, Applied Math, Computer Science, or a related field.
  • Expected graduation May – December 2025 applicants only.
  • Available to work up to 40 hours per week during a 10–12 week internship between May and September 2025.
  • Minimum 3.0 GPA.
  • Strong Experience with Python libraries for time series modeling and machine learning (e.g., StatsModels, Scikit-learn, NumPy, Pandas, XGBoost, PyTorch).
  • Strong understanding of Spark and basic working knowledge of SQL.
  • Solid understanding of time series forecasting, anomaly detection, and sequence modeling fundamentals.
  • Familiarity with model evaluation metrics and hyperparameter tuning for time series models.
  • Excellent written and verbal communication skills, with ability to document and present results clearly.
  • Highly motivated, self-directed, and capable of working in a collaborative and fast-paced environment.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position is $19.00 an hour.

Working Conditions

  • Work is performed in an office environment with low to moderate noise levels.
  • Position requires regular, continuous use of computer.
  • Position requires regular interaction with team members through the following methods: in-person, phone, WebEx, Slack, or email.
  • This is a hybrid position; employees are expected to be in the office three days per week (Monday, Tuesday, and Thursday) with the option of working remotely two days (Wednesday and Friday).
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$39520K

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What You Should Know About Data Science Intern - Summer 2025, PlanetArt

Are you ready to kickstart your career in data science? PlanetArt is thrilled to announce an exciting opportunity for a Data Science Intern for Summer 2025! Join us for a dynamic internship focused on time series modeling and forecasting where you’ll gain hands-on experience in prototyping and implementing real-time analytics solutions. Your role will involve evaluating forecasting models, engaging in exploratory data analysis, and developing model pipelines using essential Python libraries like StatsModels, Scikit-learn, and Pandas. You’ll also dive deep into Spark and SQL for data ingestion and preprocessing, allowing you to enhance your technical skill set in real-world applications. Working alongside a collaborative team of analysts, engineers, and business stakeholders, you’ll have the chance to transform complex forecasting results into meaningful insights. Plus, you’ll contribute to the visualization process, using tools like Jupyter and Tableau to communicate findings effectively. As a Data Science Intern at PlanetArt, you'll be expected to work full-time from Monday to Friday for up to 40 hours a week, so it's crucial to align your schedules without any conflicts. We can't wait for you to grow your expertise in a supportive environment while staying updated on industry trends. If you’re currently enrolled in a relevant degree program and have a GPA of 3.0 or higher, we encourage you to apply—let’s make a data-driven impact together!

Frequently Asked Questions (FAQs) for Data Science Intern - Summer 2025 Role at PlanetArt
What are the responsibilities of a Data Science Intern at PlanetArt?

As a Data Science Intern at PlanetArt, you will engage in a variety of responsibilities including prototyping time series forecasting models, conducting exploratory data analysis, developing model pipelines with Python, and collaborating with cross-functional teams to provide actionable insights based on your analyses. You'll also work with Spark and SQL for data preprocessing and contribute to the visualization of model results.

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What qualifications do I need to apply for the Data Science Intern position at PlanetArt?

To be eligible for the Data Science Intern position at PlanetArt, you must be currently enrolled in a Bachelor’s or Master’s program related to Data Science, Statistics, Applied Math, or Computer Science. We're looking for candidates with a minimum GPA of 3.0, strong experience with Python libraries for machine learning, and a solid understanding of time series concepts.

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How many hours per week will a Data Science Intern work at PlanetArt?

The Data Science Intern will work up to 40 hours per week during the internship period which typically lasts from May to September 2025. It's a full-time position, and working hours are usually from 9 AM to 5 PM, Monday through Friday.

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Is the Data Science Intern position at PlanetArt remote or in-office?

The Data Science Intern position at PlanetArt is a hybrid role. Interns are expected to be in the office three days a week, specifically on Monday, Tuesday, and Thursday, while they have the flexibility to work remotely on Wednesday and Friday.

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What tools and technologies will I be using as a Data Science Intern at PlanetArt?

In your role as a Data Science Intern at PlanetArt, you will work with a variety of tools and technologies, including Python libraries such as StatsModels, Scikit-learn, NumPy, Pandas, XGBoost, and PyTorch. Additionally, you'll utilize Spark and SQL for data processing and tools like Jupyter, Streamlit, and Tableau for data visualization.

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Common Interview Questions for Data Science Intern - Summer 2025
Can you explain the concept of time series forecasting?

Time series forecasting involves predicting future values based on previously observed values. It uses historical data points collected at regular intervals, and models such as ARIMA or exponential smoothing can be applied. Be prepared to discuss techniques you are familiar with and how you have applied them in projects.

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What experience do you have with Python libraries used in data science?

Discuss your hands-on experience with relevant Python libraries like Pandas for data manipulation, NumPy for numerical computations, and Scikit-learn for machine learning. Give specific examples of projects where these tools were utilized to solve data challenges.

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How would you approach exploratory data analysis (EDA)?

In your answer, highlight the steps of EDA including data cleaning, visualizations, identifying patterns, and summarizing key statistics. Discuss how you've used tools like Matplotlib or Seaborn for visualizations to derive insights from data sets.

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What are some common metrics used in model evaluation?

Mention metrics relevant to forecasting models such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared. Explain how you would use these metrics to assess the performance of your model and make necessary adjustments.

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Can you share a project where you applied anomaly detection?

Detail a specific project, focusing on the methods you used for anomaly detection and how you validated your findings. Talk about any challenges faced and how you resolved them to ensure accurate results.

Join Rise to see the full answer
What do you understand by hyperparameter tuning?

Hyperparameter tuning involves optimizing the settings of your machine learning algorithms to improve performance. Discuss techniques like grid search or random search and provide examples of how you've implemented them to enhance model accuracy.

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How do you stay updated on advancements in data science?

Share your strategies for keeping current, such as attending webinars, participating in online courses, following data science blogs, or engaging in community discussions on platforms like Kaggle or LinkedIn.

Join Rise to see the full answer
Describe your experience with SQL in data processing.

Discuss your proficiency in SQL for querying databases, highlighting specific tasks like data extraction, transformation, and loading (ETL). Provide examples of projects where you've successfully utilized SQL to manage and analyze data.

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What is model overfitting and how can it be avoided?

Overfitting occurs when a model learns noise in the training data rather than the actual signal, leading to poor performance on unseen data. Mention techniques such as cross-validation, regularization, and pruning trees in decision tree algorithms to prevent overfitting.

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How would you communicate complex data insights to non-technical stakeholders?

Emphasize the importance of clarity and simplicity in your communication strategy. Share examples of visualizations you've created and how you have tailored your message to the audience, ensuring that actionable insights are clearly conveyed.

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Through our network of websites and mobile apps, PlanetArt gives consumers the opportunity to design personalized products like holiday cards, photo canvases and customized gifts that are professionally printed. We provide consumers with unmatched...

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Internship, hybrid
DATE POSTED
April 9, 2025

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