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Entry Level Data Analysis Jobs in Minnesota (NOW HIRING)

DeFiner Inc

Collaborate closely with data analysts, data engineers, and business and project stakeholders to incorporate their expertise into data science solutions. * Present and defend results to leadership ...

Pwc

AI & GenAI Data Scientist - Manager

Minneapolis, MN · On-site

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Accenture

Data Protection Sr. Analyst

Minneapolis, MN · Hybrid

$84K - $100K/yr

As a Data Protection Senior Analyst, you'll support the delivery of data protection, data ... Prior internship, academic project, or entry-level experience in security or compliance is a plus.

Pwc

Data Engineer - Senior Associate

Minneapolis, MN

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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All JobsData Analysis JobsEntry Level Data Analysis JobsEntry Level Data Analysis Jobs in Minnesota

Entry Level Data Analysis information

See Minnesota salary details

$12

$32

$60

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

As of Jun 13, 2026, the average hourly pay for entry level data analysis in Minnesota is $32.25, according to ZipRecruiter salary data. Most workers in this role earn between $20.72 and $36.01 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 Minnesota? The most popular types of Data Analysis jobs in Minnesota are:
What are popular job titles related to Entry Level Data Analysis jobs in Minnesota? For Entry Level Data Analysis jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Analysis jobs in Minnesota look for? The top searched job categories for Entry Level Data Analysis jobs in Minnesota are:
What cities in Minnesota are hiring for Entry Level Data Analysis jobs? Cities in Minnesota with the most Entry Level Data Analysis job openings:
Entry Level Data Analysis jobs near you
Infographic showing various Entry Level Data Analysis job openings in Minnesota as of June 2026, with employment types broken down into 60% Full Time, 22% Part Time, 4% Temporary, and 14% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $67,077 per year, or $32.2 per hour.
Entry Level Data Scientist

Entry Level Data Scientist

DeFiner Inc

Full-time

Posted 4 hours ago

Job description

Job Description
  • Work closely with engineering and marketing teams to identify and answer important product questions to drive business growth.
  • Create machine learning solutions for a diverse set of business problems.
  • Employ structured approaches to leveraging large data sets to uncover new insights.
  • Collaborate closely with data analysts, data engineers, and business and project stakeholders to incorporate their expertise into data science solutions.
  • Present and defend results to leadership audiences, both technical and non-technical.
  • Our team philosophy encourages knowledge sharing so you will contribute to the research community through technical papers and presentations published both internally and externally.
Tech Stack
  • SQL
  • Python
  • Jupyter Notebook
  • (Optional) R script
Experience & Qualifications
  • Passion in modern technology and ability to work in a start-up environment.
  • Efficient on Jupyter Notebook
  • Good mathematic and algorithm background
  • Strong influencing skills essential. Capable of assertively interacting with business stakeholders and counterparts in order to resolve day to day issues.
  • Highly organized individual with attention to detail and excellent ability to execute on deliverables.
Employment Type: FULL_TIME

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