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Internship Time Series Forecasting Jobs (NOW HIRING)

Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.

Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.

Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

* Design and implement statistical and machine learning models for time-series forecasting, anomaly detection, and asset health scoring across utility networks. * Build and maintain end-to-end ML ...

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 ...

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

AI/ML Research Internship

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

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 ...

AI/ML Research Internship

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

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 ...

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Internship Time Series Forecasting information

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$11

$19

$26

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

As of Aug 15, 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 skills and qualifications are needed for an internship in time series forecasting?

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 do interns in time series forecasting do?

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.
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What are the most commonly searched types of Time Series Forecasting jobs?

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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 August 2026, with employment types broken down into 12% Internship, 63% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $41,299 per year, or $19.9 per hour.

Senior Applied Scientist - Demand Forecasting

Prodapt

Brentwood, CA • On-site

Full-time

Posted 11 days ago


Job description

Overview
Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A "Great Place To Work® Certified™" company, Prodapt employs over 6,000 technology and domain experts across the Americas, Europe, India, Africa, & Japan. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally.
We are seeking a highly skilled Senior Applied Scientist with expertise in demand forecasting, machine learning, and retail analytics to develop and optimize forecasting models at scale.
Responsibilities
  • Develop and retrain demand forecasting models as new regional markets come online
  • Adapt existing forecasting framework to regional demand signals (seasonality, buying patterns, lead times per market)
  • Calibrate forecast accuracy using federated regional data
  • Validate model quality meets go-live thresholds before each regional activation
  • Collaborate with the optimization team on inputs to the allocation engine

Requirements
  • Applied statistics, time-series forecasting (ARIMA, Prophet, neural methods)
  • Retail demand planning or demand sensing experience
  • SageMaker model training and deployment
  • Python, SQL, experience with large-scale retail datasets
  • Bachelor's degree in Computer Science, Engineering, or a related field; OR equivalent combination of education and relevant experience.
  • Hands-on 7+ years of experience asApplied Scientist with expertise in demand forecasting.
  • Ability to work independently with architectural direction from lead scientist

Preferred:
  • Supply chain or inventory management domain experience
  • Multi-market / international retail exposure