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Entry Level Data Analyst Jobs in Saco, ME (NOW HIRING)

Nextiny

Entry Level Digital Marketer

Portland, ME

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

Nextiny

Entry Level Digital Marketer

Biddeford, ME · On-site

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

Nextiny

Entry Level Digital Marketer

Biddeford, ME

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

Nextiny

Entry Level Digital Marketer

Portland, ME · On-site

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

SPECTRUM

Entry Level Sales

Portland, ME · On-site

$27K/yr

... speed data and communication solutions. Your efforts will drive meaningful connections and ... Conduct consultative needs analyses to tailor product recommendations for each prospective customer

SPECTRUM

Entry Level Sales

Portland, ME

$27K/yr

... speed data and communication solutions. Your efforts will drive meaningful connections and ... Conduct consultative needs analyses to tailor product recommendations for each prospective customer

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All JobsData Analyst JobsEntry Level Data Analyst JobsEntry Level Data Analyst Jobs in Saco, ME

Entry Level Data Analyst information

See Saco, ME salary details

$13

$34

$64

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

As of Aug 3, 2026, the average hourly pay for entry level data analyst in Saco, ME is $34.48, according to ZipRecruiter salary data. Most workers in this role earn between $22.16 and $38.51 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Entry level data analysts and data scientists can start at any age, including 40, as long as they develop relevant skills such as programming, statistics, and data visualization. Many professionals successfully transition into data roles later in their careers by gaining certifications and practical experience.

Can you work as a data analyst without 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 does an Entry Level Data Analyst do?

An Entry Level Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed decisions. They often work with spreadsheets, databases, and data visualization tools to identify trends and generate reports. Typical tasks include cleaning data, creating charts or dashboards, and supporting senior analysts or business teams with actionable insights. This role is ideal for individuals with strong analytical skills and a keen attention to detail, even if they have limited professional experience.

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

AspectEntry Level Data AnalystData Scientist
Required CredentialsBachelor's degree in data-related field; basic knowledge of SQL, Excel, and data visualization toolsBachelor's or master's degree in data science, statistics, or related field; stronger programming and statistical skills
Work EnvironmentEntry-level roles in business, finance, marketing, or healthcare sectors; focus on data reporting and visualizationMore advanced roles often in tech, research, or large organizations; focus on predictive modeling and complex analysis
Employer & Industry UsageCommon in various industries for routine data analysis tasksUsed in industries requiring advanced analytics, machine learning, and predictive insights

While Entry Level Data Analysts focus on basic data collection, cleaning, and reporting, Data Scientists handle complex modeling, machine learning, and predictive analytics. The roles differ mainly in skill level, complexity, and scope of work, but both require a strong foundation in data handling and analysis.

What are some common challenges entry level data analysts face when transitioning from academic projects to real-world business environments?

Entry level data analysts often find that real-world datasets are messier and less structured than those in academic settings, requiring more time spent on data cleaning and preparation. Additionally, business environments may prioritize actionable insights over purely statistical rigor, so learning to communicate findings to non-technical stakeholders is crucial. Collaborating within cross-functional teams and managing multiple deadlines can also be a new challenge, but these experiences help analysts develop strong problem-solving and communication skills that are valuable for career growth.

Can I be a data analyst with no experience?

Entry level data analyst positions often do not require prior professional experience, but having foundational 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.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, communication, and domain knowledge that AI cannot fully replicate. Therefore, AI is more likely to augment rather than replace entry-level data analysts.

What are the 4 types of data analyst?

Data analysts can be categorized into four main types: business analysts, who focus on understanding business needs; data scientists, who develop advanced models and algorithms; data engineers, who build and maintain data pipelines; and operations analysts, who optimize processes using data insights. Entry-level data analysts often start with business or operations analysis, developing skills in tools like Excel, SQL, and visualization software.

What Does an Entry-Level Data Analyst Do?

The job duties of an entry-level data analyst include working to collect, manage, and analyze data. In this career, your responsibilities often revolve around performing research on business or industry data to define trends or assess performance in a particular sector. As an entry-level data analyst, you usually work as part of a team of analysts and statisticians who analyze data and then create reports to show their findings to relevant executives, stakeholders, and managers. In some situations, this analysis team may recommend actions based on research results.

Can a data analyst be entry-level?

Yes, entry-level data analyst positions are common and typically require basic skills in data analysis tools like Excel, SQL, or Python, along with a relevant degree such as in statistics, mathematics, or computer science. These roles often focus on learning and developing analytical skills under supervision and may require little to no prior professional experience.

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 strong analytical thinking, basic statistical knowledge, and proficiency in data management, typically supported by a bachelor’s degree in a quantitative field. Familiarity with tools such as Microsoft Excel, SQL, and data visualization platforms like Tableau or Power BI is commonly required. Attention to detail, effective communication, and a willingness to learn help set candidates apart in this role. These skills are vital for accurately interpreting data, generating actionable insights, and clearly conveying findings to support business decisions.
More about Entry Level Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in Saco, ME? The most popular types of Data Analyst jobs in Saco, ME are:
What cities near Saco, ME are hiring for Entry Level Data Analyst jobs? Cities near Saco, ME with the most Entry Level Data Analyst job openings:
Entry Level Data Analyst jobs near you
Infographic showing various Entry Level Data Analyst job openings in Saco, ME as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $71,709 per year, or $34.5 per hour.

Jr. Data Scientist 00021

West Coast Consulting

Westbrook, ME

$45 - $48/hr

Other

Medical, Life

Posted 26 days ago

Job description

Job Description Hybrid -Westbrook, ME Job Description: The Machine Intelligence team in R&D is looking for an entry-level Data Scientist to develop machine learning solutions for the hematology analyzers. In this role, you will work on classification and clustering problems on tabular data, with solutions deployed on edge hardware in our analyzer platforms. You will work under the supervision of a senior data scientist who will guide your technical development and project execution.

We are looking for a curious, adaptable team player eager to build foundational skills in applied machine learning. What you can expect: Develop classification and clustering models on tabular data to support hematology analyzer capabilities Contribute to model development, evaluation, and iteration under the guidance of a senior data scientist Partner with senior team members to understand requirements, explore data, and validate model performance Document your work clearly so it can be reviewed, reproduced, and built upon by the team Deploy your solutions to edge hardware What you need to succeed: 0-2 years of experience applying machine learning to real-world problems (internships, research, and coursework projects count) Strong working knowledge of Python and common data science libraries (pandas, scikit-learn, NumPy) Solid foundation in statistics, machine learning, and algorithms Demonstrated understanding of classification and clustering methods for tabular data, including when to apply which approach and how to evaluate results Curiosity about the data and the underlying generating processes - a habit of asking "why" before reaching for a model A growth mindset and willingness to learn from more senior team members Ability to communicate analyses and results clearly to your immediate team Bachelor's degree in a quantitative field (statistics, computer science, math, engineering, or related); advanced degree a plus Nice to have: Exposure to deploying ML models on resource-constrained or edge hardware Familiarity with model optimization techniques (quantization, ONNX, TFLite) Experience with version control (Git) and collaborative software development practices Experience modeling data for medical, diagnostic or life sciences applications

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