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Entry Level Data Science Jobs in Freeport, ME (NOW HIRING)

Nova Analytic Labs LLC

Lab Technologist

Portland, ME · On-site

$20 - $24/hr

\n \n \n Nova Analytic Labs is seeking a highly motivated entry level scientist to join our cannabis ... Responsible for data entry of samples in the lab \n * Responsible for understanding and following ...

Nova Analytic Labs

Lab Technologist

Portland, ME · On-site

$20 - $24/hr

... scientific methods. As a startup, we are particularly interested in individuals with well-rounded ... This is an entry level job opportunity to assist with daily lab tasks, sample pickup, sample ...

WEX

Site Reliability Engineer 1

Portland, ME · On-site

$75K - $95K/yr

About the Team & Role We are looking for a highly motivated and high-potential entry-level Site ... Bachelor's degree in Computer Science, Engineering, or related field (or equivalent work experience)

All JobsData Science JobsEntry Level Data Science JobsEntry Level Data Science Jobs in Freeport, ME

Entry Level Data Science information

See Freeport, ME salary details

$10

$19

$27

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

As of Jul 16, 2026, the average hourly pay for entry level data science in Freeport, ME is $19.75, according to ZipRecruiter salary data. Most workers in this role earn between $16.68 and $22.16 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Entry level data science roles are open to candidates of all ages, including those starting a career at 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, regardless of age.

What are entry level data science jobs?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

How do I become a data scientist with no experience?

To become an entry-level data scientist with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, working on personal projects, and participating in competitions like Kaggle can demonstrate your abilities and help you gain practical experience. Earning relevant certifications and creating a strong portfolio can improve your chances of entering the field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Entry level data scientists often focus on identifying the most impactful variables or tasks to optimize model performance and efficiency.

What types of projects or tasks can I expect to work on as an entry-level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

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

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

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

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Can I get a data scientist job with no experience?

Entry-level data science positions often require some knowledge of programming languages like Python or R, and familiarity with data analysis tools. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve your chances of securing an entry-level role.
What are popular job titles related to Entry Level Data Science jobs in Freeport, ME? For Entry Level Data Science jobs in Freeport, ME, the most frequently searched job titles are:
What cities near Freeport, ME are hiring for Entry Level Data Science jobs? Cities near Freeport, ME with the most Entry Level Data Science job openings:
Entry Level Data Science jobs near you
Jr. Data Scientist 00021

Jr. Data Scientist 00021

West Coast Consulting LLC

Westbrook, ME • On-site

Other

Medical, Life

Posted 8 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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