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Time Series Analysis Jobs (NOW HIRING)

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

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 ...

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How much do time series analysis jobs pay per year?

As of Jun 17, 2026, the average yearly pay for time series analysis in the United States is $91,965.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $115,000.00 per year, depending on experience, location, and employer.

What is a Time Series Analysis job?

A Time Series Analysis job involves analyzing data points collected or recorded at specific time intervals to identify patterns, trends, and seasonal variations. Professionals in this role use statistical methods, machine learning models, and forecasting techniques to interpret historical data and make future predictions. Common applications include finance, economics, weather forecasting, and business performance analysis. Strong analytical skills, programming knowledge (e.g., Python, R), and experience with time series models like ARIMA or Prophet are typically required.

What are some common challenges faced in a Time Series Analysis role and how are they addressed?

Professionals in Time Series Analysis often encounter challenges such as handling missing or noisy data, accounting for seasonality and trends, and selecting the most appropriate modeling techniques for complex real-world problems. Addressing these challenges typically involves thorough data preprocessing, applying advanced statistical or machine learning models, and collaborating with domain experts to understand business contexts. Regularly updating models and validating forecasts also ensures accuracy and relevance. This dynamic environment helps analysts develop their expertise, adopt innovative solutions, and contribute significantly to data-driven decision-making within their organizations.

What are the key skills and qualifications needed to thrive in the Time Series Analysis position, and why are they important?

To excel in Time Series Analysis, you need a strong background in statistics, data analysis, and mathematics, often supported by a degree in statistics, economics, computer science, or a related field. Experience with programming languages such as Python or R, familiarity with statistical packages, and knowledge of specialized tools like ARIMA or machine learning libraries are highly beneficial. Attention to detail, problem-solving skills, and clear communication are important for effectively interpreting data and sharing insights with stakeholders. These competencies enable professionals to extract meaningful trends from complex datasets, inform strategic decisions, and provide valuable forecasts for businesses.

More about Time Series Analysis jobs
What cities are hiring for Time Series Analysis jobs? Cities with the most Time Series Analysis job openings:
What are the most commonly searched types of Time Series Analysis jobs? The most popular types of Time Series Analysis jobs are:
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Time Series Analysis jobs near you
Infographic showing various Time Series Analysis job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $91,965 per year, or $44.2 per hour.
Engineer -AI/ML -Time Series & Robotics

Engineer -AI/ML -Time Series & Robotics

Microvast

Houston, TX • On-site

Full-time

Posted 5 days ago

Job description

Job Summary:
Microvast is a technology innovator that designs and manufactures lithium-ion battery solutions. The AI / ML Engineer will develop and deploy machine learning algorithms to analyze multi-sensor time-series data from vehicles and robotic platforms, focusing on building robust models to enhance system performance and intelligent behavior.
Responsibilities:
• Design and implement ML models for time-series sensor data (e.g., currents, torques, IMUs, joint states, vehicle signals, cameras, GPS).
• Build and maintain data pipelines for collection, preprocessing, feature extraction, and labeling.
• Prototype algorithms in Python (e.g., PyTorch, TensorFlow) and collaborate with embedded engineers to create deployable, resource-efficient models.
• Create production level models using C++ to improve efficiency in runtime and resource use from the Python prototype
• Evaluate model performance using appropriate metrics; iterate to improve robustness and generalization across platforms and use cases.
• Work with robotics and vehicle engineers to understand requirements and convert them into concrete ML problems and model specifications.
• Support data visualization, dashboards, and tools for internal users to interpret model outputs and system behavior.
• Document models, experiments, datasets, and results to ensure reproducibility and traceability.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Experience with embedded / edge AI or model compression and optimization techniques.
• Hands-on experience with machine learning for time-series or sensor data.
• Strong proficiency in C++ and ML frameworks.
• Experience working with real-world noisy data (e.g., automotive, robotics, industrial, IoT).
• Familiarity with data science tools and workflows (NumPy, Pandas, Jupyter, etc.).
• Ability to work in a cross-functional team and communicate technical concepts clearly.
Preferred:
• Familiarity with control systems, robotics, or vehicle dynamics.
• Experience with MLOps tools (experiment tracking, model versioning, CI/CD for ML).
• Experience with ROS or other multimodal sensor data frameworks.
• Prior work in a product or R&D environment with multi-disciplinary teams.
Company:
Microvast designs, develops, and manufactures charging, battery control systems for electric vehicles with superior safety. Founded in 2006, the company is headquartered in Stafford, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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