Job Description

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.

Requirements

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.

Benefits

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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