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Internship Time Series Analysis Jobs (NOW HIRING)

Ceribell, Inc

Data Scientist

Sunnyvale, CA

Use time-series analysis, statistical signal processing and machine learning techniques to design ... Mentor and guide junior data scientists and interns, fostering their growth by providing technical ...

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

Use time-series analysis, statistical signal processing and machine learning techniques to design ... Mentor and guide junior data scientists and interns, fostering their growth by providing technical ...

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

Use time-series analysis, statistical signal processing and machine learning techniques to design ... Mentor and guide junior data scientists and interns, fostering their growth by providing technical ...

M&T Bank

Model Risk Analyst-Validation

Buffalo, NY · On-site

$91K - $101K/yr

Data Science concepts, including statistics and probability, exploratory data analysis (EDA), machine learning, model evaluation and selection, feature engineering, time series analysis, loss ...

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

As of Jul 7, 2026, the average hourly pay for internship time series analysis in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during an internship in time series analysis?

As an intern specializing in time series analysis, you will typically assist with collecting, cleaning, and analyzing temporal data using statistical software such as Python or R. Your projects may include forecasting trends, detecting anomalies, and visualizing patterns in data sets from fields like finance, healthcare, or operations. You will often collaborate with data scientists, analysts, and business stakeholders to translate findings into actionable insights, while learning to apply techniques such as ARIMA, exponential smoothing, or machine learning models. This hands-on experience is a valuable foundation for pursuing advanced roles in data science and analytics.

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

AspectInternship Time Series AnalysisData Analyst
Required CredentialsRelevant coursework, basic statistical knowledgeBachelor's degree in related field, some certifications
Work EnvironmentInternship setting, supervised projectsFull-time or part-time professional role
Industry UsageEntry-level, learning-focusedBusiness, finance, healthcare, and more

Internship Time Series Analysis is an entry-level, learning-focused role typically performed during internships, emphasizing foundational skills in analyzing time-based data. In contrast, Data Analysts are more experienced professionals responsible for interpreting data to inform business decisions. While both roles involve data analysis, internships are more about gaining experience, whereas Data Analysts perform ongoing, complex analysis in various industries.

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

To thrive as an Internship Time Series Analysis, you need a solid grounding in statistics, data analysis, and proficiency in mathematical concepts, usually supported by coursework in mathematics, statistics, or data science. Familiarity with technical tools such as Python or R, and experience with libraries like pandas, NumPy, and statsmodels, as well as data visualization platforms, are highly valuable. Analytical thinking, problem-solving abilities, and strong communication skills set candidates apart in interpreting results and presenting findings. These skills ensure accurate modeling, effective data-driven insights, and clear communication of complex temporal patterns for impactful business or research decisions.

What is an internship in time series analysis?

An internship in time series analysis is a temporary position, often for students or recent graduates, where you gain hands-on experience analyzing data that is collected over time. Interns typically work with datasets to identify trends, patterns, and make forecasts using statistical and machine learning techniques. The role may involve using tools like Python, R, or specialized software to clean data, build models, and visualize results. It’s a valuable opportunity to apply theoretical knowledge from coursework to real-world problems in industries such as finance, economics, or technology.
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Internship Time Series Analysis jobs near you
Data Scientist

Data Scientist

Ceribell, Inc

Sunnyvale, CA

Other

Posted 19 days ago

Job description

Position Overview: 

We are looking for a talented data scientist/algorithm engineer who is passionate about biomedical applications and has a strong background in machine learning, pattern recognition, signal processing and time-series analysis. The successful candidate will join the data science team and will be responsible for design and development of new state-of-the-art classification algorithms that will take the field of EEG neurodiagnostics to the next level.

What you'll do:

  • Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various neurological indications
  • Analyze data for trends and patterns, and interpret data with a clear objective in mind
  • Collaborate with business and clinical stakeholders to define project needs and communicate results of the models/analytical solutions designed
  • Select and implement appropriate evaluation metrics to assess the performance of algorithms and models, considering both technical accuracy and clinical relevance.
  • Document and validate models and perform statistical analysis to comply with regulatory requirements for medical device algorithms
  • Mentor and guide junior data scientists and interns, fostering their growth by providing technical direction, feedback, and support
  • Manage multiple projects independently, effectively prioritizing tasks and aligning deliverables with key milestones to ensure timely and successful outcomes
  • Stay updated with the latest advancements in machine learning and neurodiagnostics to ensure the algorithms are state-of-the-art

What We're Looking For: 

  • PhD in Electrical Engineering, Computer Science, Statistics, or equivalent disciplines
  • 7+ years of relevant research and/or industry experience in signal processing, filtering, statistical data analysis, time-series analysis, pattern recognition, feature engineering, machine learning and algorithm development
  • Proficient in Python and/or Matlab and/or R or similar programming languages
  • Experience and interest in biological signal processing and algorithm development for biomedical applications
  • Strong analytical skills, detail-oriented and collaborative
  • Experience with large-scale datasets, including preprocessing, cleaning, and handling noisy or imbalanced data in a biomedical context
  • Proven ability to work independently, define scope and and manage complex technical projects from concept to deployment
  • Experience with advanced machine learning techniques, such as deep learning architectures (e.g., CNNs, RNNs) and their application to time-series data
  • Strong preference for experience in neurodiagnostics or EEG data processing and algorithm development

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