1

Exploratory Data Analysis Jobs (NOW HIRING)

Responsibilities Data Scientist, I Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, machine learning ...

Responsibilities Data Scientist, I Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, machine learning ...

Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection ...

Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection ...

Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection ...

Exploratory Data Analysis (EDA): Analyzing data to uncover hidden patterns, correlations, and trends. Modeling and Machine Learning: Developing algorithms, designing predictive models, and training ...

Data Engineer

Annapolis Junction, MD · On-site

$117K - $140K/yr

The role involves managing data storage, transport, security, and compliance, as well as performing exploratory data analysis on raw data. Responsibilities : • orchestrate complex operational data ...

Apply exploratory data analysis, statistical techniques, and basic predictive modeling to large, multi-source datasets to identify trends, correlations, and outliers that support operational and ...

Apply exploratory data analysis, statistical techniques, and basic predictive modeling to large, multi-source datasets to identify trends, correlations, and outliers that support operational and ...

Apply exploratory data analysis, statistical techniques, and basic predictive modeling to large, multi-source datasets to identify trends, correlations, and outliers that support operational and ...

Showing results 21-40

Exploratory Data Analysis information

See salary details

$34K

$82.6K

$136K

How much do exploratory data analysis jobs pay per year?

As of Aug 18, 2026, the average yearly pay for exploratory data analysis in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is exploratory data analysis?

An Exploratory Data Analysis (EDA) job involves analyzing and summarizing datasets to uncover patterns, relationships, and anomalies before applying formal modeling techniques. Professionals in this role use statistical methods and visualization tools to interpret data insights, assess data quality, and guide decision-making. EDA helps organizations understand their data better, ensuring that downstream analysis and machine learning models are built on a strong foundation.

What does someone in exploratory data analysis do?

Professionals in Exploratory Data Analysis spend their days gathering, cleaning, and examining data sets to identify patterns, trends, and potential outliers. They use statistical and visualization tools to create reports and dashboards that help stakeholders understand the data’s implications. Collaboration with data engineers, business analysts, and management is common to ensure that the analyses address real business questions. Additionally, they often refine data collection processes and suggest improvements based on their findings, contributing to more efficient and insightful data workflows.

What are the key skills and qualifications needed for exploratory data analysis?

To thrive in Exploratory Data Analysis, you need a strong background in statistics, data visualization, and data manipulation with a relevant degree such as in statistics, mathematics, or computer science. Proficiency with tools like Python (pandas, matplotlib, seaborn), R, SQL, and data visualization platforms such as Tableau is highly valued, and certifications in data analytics can be beneficial. Strong problem-solving skills, attention to detail, and the ability to communicate insights clearly are essential soft skills for this role. These abilities ensure that analysts can interpret complex datasets, uncover valuable trends, and present findings to inform business decisions.

What is an exploratory data analyst?

An exploratory data analyst is a professional who examines and summarizes data sets to identify patterns, trends, and relationships. They use statistical tools and programming languages like Python or R to visualize data and support decision-making processes.
More about Exploratory Data Analysis jobs

What are the most commonly searched types of Exploratory Data Analysis jobs?

The most popular types of Exploratory Data Analysis jobs are:

What states have the most Exploratory Data Analysis jobs?

States with the most job openings for Exploratory Data Analysis jobs include:

Infographic showing various Exploratory Data Analysis job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Senior Data Scientist - Forecasting, AI Development

Jobtailor

Manhattan, NY • On-site

$120 - $180/hr

Other

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


Job description

Responsibilities
  • Own and evolve key forecasting assets, applying modern statistical, machine learning, and AI-driven approaches to improve accuracy, scalability, and business value
  • Integrate AI into forecasting workflows, such as feature engineering, exploratory data analysis, and model development
  • Shape next-generation forecasting capabilities while driving measurable impact across the organization
Requirements
  • 3+ years of experience in data science, forecasting, or a related quantitative field
  • Strong expertise in time series forecasting methods, including statistical and machine learning approaches
  • Experience with ensemble modeling techniques and model evaluation strategies
  • Proven experience with hierarchical or multi-level forecasting
  • Strong programming skills in Python (e.g., pandas, NumPy, scikit-learn, statsmodels, or similar libraries)
  • Experience applying AI/ML techniques to forecasting workflows, including feature engineering and exploratory data analysis
  • Strong problem-solving, communication, and stakeholder management skills
#J-18808-Ljbffr