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Time Series Analysis Jobs (NOW HIRING)

acunor

Data Scientist - TIme Series

Philadelphia, PA · Hybrid

This role focuses on forecasting, causal inference, customer behavior analytics, and statistical ... Build and deploy advanced time series forecasting models including ARIMA, SARIMA, VAR, and state ...

CloudDevs

This fully remote role requires strong expertise in Python, statistical modelling, and time series analysis. Candidates should have a passion for solving real-world problems and be able to work ...

Info Way Solutions

Scrum Master / PM (Time Series)

Fremont, CA · On-site

$56.50 - $75.25/hr

Requirement Analysis: * Elicit and analyze business requirements from internal stakeholders regarding financial time series data management and analysis. * Translate business needs into detailed ...

Diverse Lynx

Data Engineer- PySpark/Apache Flink

Irving, TX · On-site

$109.90K - $132K/yr

... time-series analysis) Data Engineering AutomationClean| normalize| and enrich alarm data from multiple sources Integrate data from OSS| EMS| NMS| CMDB| and performance systemsKey responsibilitiesData ...

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

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 May 28, 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 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.

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.
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Time Series Analysis jobs near you
Infographic showing various Time Series Analysis job openings in the United States as of May 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.
Data Scientist - TIme Series

Data Scientist - TIme Series

acunor

Philadelphia, PA • Hybrid

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Senior Data Scientist – Econometrics & Time Series

Location: Philadelphia, PA (Hybrid – 2–3 Days Onsite)

Type: Full-Time

Role Overview

We are seeking a Senior Data Scientist with strong expertise in Econometrics and Time Series Analysis to support advanced analytics initiatives for a large Telecommunications environment. This role focuses on forecasting, causal inference, customer behavior analytics, and statistical modeling using large-scale datasets.

The ideal candidate will have deep hands-on experience with econometric techniques, probabilistic modeling, and time series forecasting frameworks, along with strong Python and SQL skills.

Key Responsibilities

  • Build and deploy advanced time series forecasting models including ARIMA, SARIMA, VAR, and state-space models
  • Apply econometric techniques such as WLS, regression diagnostics, panel data models, and causal inference methods
  • Develop Bayesian and probabilistic models for uncertainty estimation and decision-making
  • Utilize Markov chains and stochastic modeling techniques for behavioral and sequential data analysis
  • Translate complex business problems into scalable analytical solutions and actionable insights
  • Work with large-scale datasets using Databricks and modern analytics platforms
  • Partner with business and technical stakeholders to drive data-driven decision making
  • Mentor junior data scientists and promote best practices in statistical modeling and experimentation

Required Skills

  • Strong expertise in Econometrics and Time Series Analysis
  • Hands-on experience with:
  • ARIMA, SARIMA, VAR, forecasting models
  • Regression diagnostics, WLS, panel data models
  • Causal inference and experimentation frameworks
  • Bayesian statistics and probabilistic modeling
  • Markov chains and stochastic processes
  • Strong programming skills in Python and SQL
  • Experience with Databricks or similar big data environments
  • Excellent communication and stakeholder management skills

Nice to Have

  • Experience with machine learning models and predictive analytics
  • Knowledge of feature engineering, model validation, and performance tuning
  • Exposure to ML pipelines and MLOps concepts
  • Telecommunications domain experience is a plus
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About Acunor

Sourced by ZipRecruiter

Acunor provides high quality digital engineers in the field of Java Full Stack Programming, Pega, Appian, Power BI, Salesforce, DevOps, No-Code & Low-Code, Data Science, Analytics, Data Base and Cloud Native solutions. ​We specialize in providing Java Full Stack Engineers, BPM (Pega, Appian) Consultants, Salesforce Consultants, AWS/Azure/GCP Engineers, Data Scientists, Technical PMs, Program and Engagement Managers. ​Management comprises of highly experienced and seasoned technology executives with vast expertise in Large Scale Development Projects, Cloud Native Solutions and Managed Services.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Princeton, NJ, US

Year founded

2016

Social media

Twitter

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