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Exploratory Data Analysis Eda Jobs (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · On-site +1

$107K - $182K/yr

... exploratory data analysis (EDA) techniques to uncover patterns, identify anomalies, and generate insights from datasets. 6. Applying stochastic optimization methods to optimize processes and systems ...

The Campbell?s Company

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

... exploratory data analysis (EDA) to identify patterns, anomalies, and key demand driversInsight GenerationTranslate data into actionable insights to understand the impact of promotions, pricing, and ...

Spatial Front, Inc

Data Scientist

Arlington, VA · On-site

Responsibilities : • Develop, train, validate, and deploy machine learning and statistical models to address program analytical challenges. • Perform exploratory data analysis (EDA) to identify ...

Cayuse Holdings, LLC

$28 - $30/hr

Exploratory Data Analysis (EDA): Perform exploratory data analysis using notebooks like Azure Machine Learning Notebooks or Azure Databricks to derive actionable insights. * Data Quality Assessments:

Purple Drive Technologies

Data Scientist

Plano, TX · On-site

Exploratory Data Analysis (EDA) * Analyze datasets to identify patterns, correlations, and trends. * Develop hypotheses and validate findings using statistical techniques. Modeling & Machine Learning

Aroha Technologies Inc

AI Architect

Winters, TX

$60.50 - $78/hr

Conduct exploratory data analysis (EDA) to identify patterns, trends, and insights in large datasets. Deploy ML models into production using MLflow, Databricks Workflows, or other MLOps pipelines.

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Exploratory Data Analysis Eda information

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How much do exploratory data analysis eda jobs pay per year?

As of Jun 16, 2026, the average yearly pay for exploratory data analysis eda 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.

Will AI replace data analysts?

AI tools can automate routine data analysis tasks, but the role of a data analyst involves interpreting insights, understanding context, and communicating findings, which currently require human judgment. Data analysts who develop skills in programming, statistical methods, and data visualization tools are better positioned to adapt to technological changes and leverage AI as a complement to their work.

What is the salary of exploratory data analyst?

The average salary for an exploratory data analyst typically ranges from $60,000 to $85,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts with skills in tools like Python, R, or SQL can earn higher salaries.

What are the key skills and qualifications needed to thrive in Exploratory Data Analysis (EDA), and why are they important?

To excel in Exploratory Data Analysis (EDA), you need a solid foundation in statistics, data visualization, and data wrangling, typically supported by a degree in data science, statistics, or a related field. Proficiency with technical tools such as Python (pandas, matplotlib, seaborn), R, and data visualization platforms is essential. Strong analytical thinking, curiosity, and effective communication skills help interpret data patterns and share insights with stakeholders. These skills are crucial for uncovering trends, informing decision-making, and ensuring data-driven project success.

What are some common challenges faced by professionals working in Exploratory Data Analysis (EDA) roles?

Professionals in Exploratory Data Analysis (EDA) often encounter challenges such as dealing with incomplete or messy data, selecting appropriate visualization techniques, and identifying meaningful patterns without introducing bias. EDA specialists must also balance the need for in-depth analysis with tight deadlines, especially when collaborating with data scientists and business stakeholders who rely on their insights to guide modeling decisions. Developing strong communication skills is essential, as EDA findings must be clearly presented to both technical and non-technical team members.

Do data analysts do EDA?

Yes, data analysts commonly perform exploratory data analysis (EDA) as a key step in understanding data, identifying patterns, and preparing datasets for modeling. EDA involves using tools like Excel, SQL, or Python libraries such as pandas and matplotlib to visualize and summarize data before further analysis or reporting.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills in data analysis, programming, and tools like Excel, SQL, and Python. Many professionals successfully transition into data analysis later in their careers by gaining relevant certifications and experience.

What is the difference between Exploratory Data Analysis Eda vs Data Analyst?

AspectExploratory Data Analysis EdaData Analyst
Primary FocusAnalyzing data to uncover patterns and insightsInterpreting data to support business decisions
Skills RequiredStatistical analysis, data visualization, programming (Python/R)Data manipulation, reporting, communication skills
Tools UsedPython, R, SQL, TableauExcel, SQL, BI tools, visualization software
Work EnvironmentData science teams, research projectsBusiness units, reporting teams

Exploratory Data Analysis (Eda) focuses on understanding data through statistical and visual methods, often performed by data scientists. Data Analysts interpret data to generate reports and support decision-making. While both roles work with data, Eda is more technical and exploratory, whereas Data Analysts focus on delivering actionable insights to stakeholders.

What is exploratory data analysis (EDA)?

Exploratory Data Analysis (EDA) is a process in data science that involves summarizing, visualizing, and understanding datasets before applying formal modeling techniques. EDA helps identify patterns, trends, anomalies, and relationships within the data, making it easier to formulate hypotheses and select appropriate statistical tools. Common EDA techniques include data visualization (such as histograms, scatter plots, and box plots), descriptive statistics, and handling missing values or outliers. This step is crucial for ensuring data quality and guiding further analysis.
Infographic showing various Exploratory Data Analysis Eda job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 75% Full Time, and 23% Part Time. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Applied Machine Learning Scientist Intern - PhD

Applied Machine Learning Scientist Intern - PhD

Marvell Technology, Inc.

Santa Clara, CA • On-site

Full-time

Medical, Dental, Vision, Retirement

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

Job description

About Marvell
Marvell's semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities.
At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.
Your Team, Your Impact
Marvell IT - Data Analytics Team is at the forefront of driving Marvell's Data Intelligence, Strategy, and Architecture initiatives. As a high-visibility team, we deliver critical data insights and analytics solutions to the operations and leadership group that empower data-driven decision-making at the highest levels.
Our team is responsible for executing global, high-impact projects that add significant value across the organization. By leveraging cutting-edge data analytics technologies and methodologies, we ensure that Marvell remains a leader in harnessing data for business advantage.
What You Can Expect
We are seeking a motivated and enthusiastic Data Science Intern to join our data and analytics team. This internship is an excellent opportunity for individuals looking to apply their academic knowledge of data science in a real-world setting. The intern will work closely with our experienced data scientists, engineers, and business stakeholders to develop data-driven insights and build predictive models that address business challenges.
Key Responsibilities:
  • Collaborate with the data science team to gather, clean, and preprocess data from various sources.
  • Perform exploratory data analysis (EDA) to identify patterns, trends, and relationships within large datasets.
  • Assist in building and optimizing machine learning models to solve business problems.
  • Develop data visualizations, dashboards, and reports using tools like Power BI or Python libraries.
  • Present findings and recommendations to stakeholders in a clear and concise manner.
  • Work with large-scale data sets using SQL, Python for data manipulation and analysis.
  • Support the development and deployment of machine learning models in production .Support data integration and data engineering activities, including ETL processes, within Snowflake or Databricks environments.

What We're Looking For
  • Pursuing degree in Computer Science, Data Science, or related field
  • Proficiency in Python for data analysis, including libraries like pandas, NumPy, scikit-learn, and matplotlib etc.
  • Knowledge of SQL for querying databases.
  • Understanding of basic statistical concepts and machine learning algorithms (e.g., regression, classification, clustering).
  • Familiarity with data visualization tools such as Power BI or Python-based visualization libraries (e.g., seaborn, Plotly).
  • Proficiency in data preprocessing, data transformation, and exploratory data analysis (EDA) to extract valuable insights from raw datasets.
  • Familiarity with Generative AI and Large Language Models (LLMs) is a plus.

Expected Base Pay Range (USD)
0 - 0, $ per hour.
The successful candidate's starting base pay will be determined based on job-related skills, experience, qualifications, work location and market conditions. The expected base pay range for this role may be modified based on market conditions.
Additional Compensation and Benefit Elements
Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life's most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights for our interns: medical, dental, and vision coverage, perks and discounts, robust mental health resources to prioritize emotional well-being, and paid holidays. Additional compensation may be available for intern PhD candidates. We look forward to sharing more with you during the interview process.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.
Any applicant who requires a reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com.
Interview Integrity
To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews.
These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process.
This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.
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