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Internship Time Series Forecasting Jobs (NOW HIRING)

Strong Time Series forecasting, ML, deep learning and standard statistical methods to evaluate models. Experience working on supply chain projects. We are seeking a highly skilled Data Scientist to ...

At Amazon, our Demand Forecasting team is tackling one of the most ambitious challenges in applied time series research: building large-scale foundation models that generalize across an enormous and ...

The ideal candidate will have a strong background in time series forecasting, anomaly detection, event classification, and correlation ML algorithms. Additionally, experience in integrating with ...

We're seeking interns who care about outcomes, think in systems, and make data-driven decisions. If ... Next-Gen Time-Series Forecasting for Sleep: Push state of the art on multivariate forecasting to ...

This role requires hands-on experience with time series forecasting, anomaly detection, event classification, and correlation ML algorithms. Additionally, experience in integrating with large ...

We're seeking interns who care about outcomes, think in systems, and make data-driven decisions. If ... Next-Gen Time-Series Forecasting for Sleep: Push state of the art on multivariate forecasting to ...

Senior Data Scientist

Manhattan, NY · On-site

$60 - $65/hr

Build forecasting and predictive models using time-series techniques. * Develop anomaly detection and recommendation engine capabilities. * Perform feature engineering, model validation, and back ...

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Internship Time Series Forecasting information

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How much do internship time series forecasting jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for internship time series forecasting in the United States is $19.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.07 and $22.36 per hour, depending on experience, location, and employer.

What is the difference between Internship Time Series Forecasting vs Data Analyst?

AspectInternship Time Series ForecastingData Analyst
Required CredentialsBasic knowledge of statistics, programming, and time series conceptsBachelor's degree in data-related fields, some roles may require certifications
Work EnvironmentInternship setting, often in finance, retail, or tech companiesFull-time or part-time roles in various industries, including finance, healthcare, and marketing
Employer & Industry UsageUsed for entry-level training and project support in forecasting tasksUsed for data analysis, reporting, and decision-making across industries

Internship Time Series Forecasting focuses on entry-level, project-based work involving forecasting models, while Data Analysts perform broader data analysis tasks, including reporting and insights. Both roles require analytical skills but differ in scope and experience level.

What are the key skills and qualifications needed to thrive as an Internship Time Series Forecasting, and why are they important?

To thrive as an Internship Time Series Forecasting, you need a solid background in statistics, data analysis, and programming, often supported by coursework or experience in mathematics, economics, or computer science. Familiarity with statistical software and programming languages such as Python or R, as well as tools like pandas, NumPy, and forecasting libraries (e.g., Prophet, ARIMA), is typically required. Strong problem-solving skills, attention to detail, and effective communication set candidates apart in this analytical role. These abilities are crucial for accurately analyzing data trends, communicating insights, and delivering reliable forecasts that support business decisions.

What is an Internship in Time Series Forecasting?

An Internship in Time Series Forecasting is a temporary position that allows students or recent graduates to gain hands-on experience analyzing and predicting data points over time. Interns typically work with historical datasets to identify trends, seasonality, and patterns, often using statistical or machine learning models. These internships provide valuable exposure to real-world forecasting challenges in industries such as finance, retail, or technology, and help interns develop both technical and analytical skills. Interns may also collaborate with data scientists and business analysts to support decision-making processes.

What are some typical projects or tasks an intern in time series forecasting might work on during their internship?

As an intern in time series forecasting, you can expect to work on projects involving the analysis and modeling of sequential data—such as sales figures, stock prices, or sensor readings. Common tasks include cleaning and visualizing time-based datasets, applying statistical and machine learning models (like ARIMA or LSTM), and evaluating model performance. Interns often collaborate with data scientists and analysts to interpret results, present findings, and help integrate forecasting models into business processes. These experiences provide valuable hands-on exposure to both the technical and collaborative aspects of data science.
More about Internship Time Series Forecasting jobs
What cities are hiring for Internship Time Series Forecasting jobs? Cities with the most Internship Time Series Forecasting job openings:
What are the most commonly searched types of Time Series Forecasting jobs? The most popular types of Time Series Forecasting jobs are:
What states have the most Internship Time Series Forecasting jobs? States with the most job openings for Internship Time Series Forecasting jobs include:
Infographic showing various Internship Time Series Forecasting job openings in the United States as of July 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $41,299 per year, or $19.9 per hour.
Data Science Machine Learning Internship (Summer 2027)

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Stamford, CT

Full-time

Posted 3 days ago


Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.