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Internship Time Series Forecasting Jobs (NOW HIRING)

Inherent Technologies

Data Scientist

Chandler, AZ · Remote

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 ...

Amazon

Data Scientist, Demand Forecasting

Bellevue, WA · On-site

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 ...

Eight Sleep

AI/ML Research Internship

San Francisco, CA · On-site

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 ...

Redolent, Inc.

AI/ML Engineer

Phoenix, AZ · On-site

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

Eight Sleep

AI/ML Research Internship

San Francisco, CA · On-site

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 ...

Redolent, Inc.

Sr, ML Architect

Washington, DC · On-site

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 ...

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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 2, 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.
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Internship Time Series Forecasting jobs near you
Infographic showing various Internship Time Series Forecasting job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 72% Full Time, and 27% Part Time. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $41,299 per year, or $19.9 per hour.
Adjunct Instructor in Time Series Forecasting and Operational Analytics

Adjunct Instructor in Time Series Forecasting and Operational Analytics

Brandeis University

Brandeis, CA

$6.5K/mo

Part-time

Posted 6 hours ago

Job description

Brandeis University's Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 135 Time Series Forecasting and Operational Analytics for the Fall-2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics.

This course will cover predictive modeling and forecasting under uncertainty, including ARIMA, Prophet, and deep learning approaches for sustainable operations.

Core Course Responsibilities Summary

  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.

  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.

  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.

  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:

  • Required:

    • Advanced degree (Masters or Ph.D) in Statistics, Operational Research, Data Science or a related field.

    • Professional experience applying forecasting methods to operational demands, planning, or in sustainability contexts.

    • Expertise in time series analysis and forecasting under uncertainty, including ARMIA and modern machine learning approach.

    • At least 1 year of teaching or training experience (preferably online/asynchronous)

    • Experience with online instruction

    • Excellent communication and teaching skills in an online learning environment.

  • Preferred:

    • Prior online teaching experience at the graduate level

    • Knowledge of global learner personas and culturally responsive pedagogy

    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:

A cover letter highlighting relevant qualifications and teaching experience.

A current CV or resume.

Contact information for three professional references.

Application review begins June 1, 2026 though we will continue to accept submissions on an ongoing basis.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

Compensation for this positon is: $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

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