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Entry Level Data Analysis Jobs in Ohio (NOW HIRING)

We are seeking an enthusiastic and detail-oriented Entry-Level Data Analyst to join our team. The candidate will help collect, organize, and analyze data to support business decisions. This position ...

Business Data Analyst (Junior)

Cleveland, OH · On-site

$25.75 - $34.50/hr

This role is ideal for entry level candidates or individuals starting their career in business analysis. Responsibilities · Collect, clean, and analyse business data from multiple sources. · Assist ...

Data Analysis: Apply thorough technical knowledge to large datasets, conducting exploratory data ... Job Schedule Full time Job Number R000135859 Job Segmentation Entry Level Starting Pay / Salary ...

They are seeking an entry-level Software Engineer to support NASIC at Wright-Patterson AFB by writing and maintaining source code repositories for data analysis tools that aid in producing technical ...

Perform exploratory data analysis to identify patterns, anomalies, and actionable insights ... Previous BI or analytics internship or entry-level work experience. * Exposure to Manufacturing ...

Be Seen First

This role is ideal for entry-level or early-career engineers who want hands-on experience working ... Analyze warranty data and customer concerns * Perform root cause analysis (RCA) on defects

Be Seen First

This role is ideal for entry-level or early-career engineers who want hands-on experience working ... Analyze warranty data and customer concerns * Perform root cause analysis (RCA) on defects

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Entry Level Data Analysis information

See Ohio salary details

$12

$31

$58

How much do entry level data analysis jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for entry level data analysis in Ohio is $31.30, according to ZipRecruiter salary data. Most workers in this role earn between $20.10 and $34.95 per hour, depending on experience, location, and employer.

What are some common challenges entry-level data analysts face when starting out, and how can they overcome them?

Entry-level data analysts often encounter challenges such as learning new data tools, understanding unfamiliar datasets, and translating business questions into analytical tasks. It's common to feel overwhelmed by the variety of software (like Excel, SQL, or Python) and the pace of real-world projects. To overcome these hurdles, new analysts should proactively seek mentorship, participate in team discussions, and take advantage of online resources or internal training. Regular collaboration with colleagues and asking clarifying questions can help build confidence and ensure successful project contributions.

How to get hired as an entry-level data analyst?

To get hired as an entry-level data analyst, candidates should develop foundational skills in data analysis tools like Excel, SQL, and Python or R, and build a portfolio of relevant projects. Earning certifications such as Microsoft Data Analyst Associate or Google Data Analytics can improve prospects, along with gaining internship experience or completing relevant coursework. Strong communication skills and the ability to interpret data for non-technical audiences are also important.

Can I be a data analyst with no experience?

Entry level data analyst positions often do not require prior professional experience, but having skills in Excel, SQL, or data visualization tools can improve your chances. Many employers value relevant coursework, certifications, or internships that demonstrate your ability to analyze data effectively.

What is an entry level data analyst?

An entry level data analyst is a professional who collects, processes, and performs basic analysis on data to help organizations make informed decisions. They typically work with tools like Excel, SQL, or data visualization software to organize and interpret data sets. Entry level analysts focus on tasks such as cleaning data, creating reports, and identifying trends, usually under the supervision of more experienced analysts. This role is ideal for recent graduates or individuals starting their career in data analysis.

Is 40 too late for data science?

Entry level data analysis roles are accessible at any age, including at 40 or older. Success depends on acquiring relevant skills such as proficiency in Excel, SQL, and data visualization tools, as well as building a strong portfolio and gaining practical experience. Age is less important than skills, continuous learning, and adapting to industry tools and methods.

What are the key skills and qualifications needed to thrive as an Entry Level Data Analyst, and why are they important?

To thrive as an Entry Level Data Analyst, you need foundational knowledge in statistics, data interpretation, and a relevant degree such as in mathematics, economics, or computer science. Familiarity with tools like Microsoft Excel, SQL, and data visualization platforms such as Tableau or Power BI is typically required. Strong analytical thinking, problem-solving abilities, and clear communication help you extract meaningful insights and present findings effectively. These skills are crucial for transforming raw data into actionable information that supports informed business decisions.

Is AI replacing data analysts?

AI tools are automating certain repetitive tasks in data analysis, such as data cleaning and basic reporting, but they do not replace the need for skilled data analysts. Entry-level data analysis roles still require critical thinking, domain knowledge, and interpretation skills that AI cannot fully replicate. Professionals who develop expertise in data visualization, programming, and statistical methods remain valuable in the field.

What is the difference between Entry Level Data Analysis vs Data Analyst?

AspectEntry Level Data AnalysisData Analyst
Required CredentialsAssociate's degree or relevant certificationBachelor's degree often preferred
Work EnvironmentInternships, entry-level roles, training programsFull-time positions in various industries
Employer & Industry UsageStart of career, learning phaseMid-level roles, more responsibilities
Common Search & Comparison IntentUnderstanding entry-level opportunitiesAdvancement and skill development

Entry Level Data Analysis roles are designed for beginners with minimal experience, focusing on learning foundational skills. Data Analysts typically have more experience, handle complex data projects, and contribute to strategic decision-making. The main difference lies in experience level, responsibilities, and career progression.

What are the most commonly searched types of Data Analysis jobs in Ohio? The most popular types of Data Analysis jobs in Ohio are:
What cities in Ohio are hiring for Entry Level Data Analysis jobs? Cities in Ohio with the most Entry Level Data Analysis job openings:
Infographic showing various Entry Level Data Analysis job openings in Ohio as of June 2026, with employment types broken down into 76% Full Time, 18% Part Time, 1% Temporary, and 5% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $65,111 per year, or $31.3 per hour.

Data Operations Associate

Dhalite Inc.

Columbus, OH • On-site

Other

Posted yesterday


Job description

Job Title: Data Operations Associate

Job Summary:
We are seeking an enthusiastic and detail-oriented Entry-Level Data Analyst to join our team. The candidate will help collect, organize, and analyze data to support business decisions. This position is ideal for entry level candidates or candidates looking to start their career in data analysis.

Responsibilities:
  • Collect, organize, and maintain data from different sources
  • Analyze data and prepare simple reports for management
  • Identify trends, patterns, and insights from data
  • Assist in maintaining accurate databases and records
  • Support teams by providing data-related information
  • Create charts, summaries, and presentations based on findings
  • Ensure data accuracy and consistency in reports
Requirements:
  • Bachelor’s degree in Mathematics, Statistics, Business, IT, or a related field
  • Basic knowledge of Microsoft Excel and data handling
  • Strong analytical and problem-solving skills
  • Good written and verbal communication skills
  • Attention to detail and accuracy
  • Ability to work in a team environment
  • Eagerness to learn and develop analytical skills
Preferred Skills:
  • Basic understanding of data reporting and analysis
  • Time management and organizational skills
  • Ability to handle confidential information professionally
 
 
 
 
 
 
 
 
 
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