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Entry Level Data Science Jobs in Vermont (NOW HIRING)

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Entry Level Data Science information

See Vermont salary details

$11

$20

$28

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

As of Jul 6, 2026, the average hourly pay for entry level data science in Vermont is $20.26, according to ZipRecruiter salary data. Most workers in this role earn between $17.12 and $22.74 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 the most commonly searched types of Data Science jobs in Vermont? The most popular types of Data Science jobs in Vermont are:
What are popular job titles related to Entry Level Data Science jobs in Vermont? For Entry Level Data Science jobs in Vermont, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Science jobs in Vermont look for? The top searched job categories for Entry Level Data Science jobs in Vermont are:
What cities in Vermont are hiring for Entry Level Data Science jobs? Cities in Vermont with the most Entry Level Data Science job openings:
CTIO - AI Engineer - Experienced Associate

CTIO - AI Engineer - Experienced Associate

Pwc

Montpelier, VT • On-site

$50K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

21st of 58 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Information Technology (IT)

Management Level

Associate

Job Description & Summary

The Opportunity
As a CTIO - AI Engineer - Experienced Associate, you will leverage advanced analytics and statistical techniques to transform raw data into actionable insights, driving data-driven decision-making and business growth. Within our Internal Firm Services practice, you will focus on learning and contributing to client engagements and projects, developing your skills and knowledge to deliver quality work. You will be exposed to clients, learning how to build meaningful connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources.
In this role at PwC, you will engage in exploratory and descriptive analysis, statistical modeling, and creating data visualizations to solve complex business problems and inform strategic decisions. You are expected to adapt to working with a variety of clients and team members, each presenting unique challenges and scope. Every experience is an opportunity to learn and grow, taking ownership and consistently delivering work that drives value for our clients and success as a team. As you navigate through the firm, you build a brand for yourself, opening doors to more opportunities.
Responsibilities
- Leveraging advanced analytics and statistical techniques to extract insights from large datasets
- Designing and developing robust data solutions to transform raw data into actionable insights
- Applying data science algorithms and machine learning techniques to solve complex business problems
- Building data pipelines and confirming data quality for informed decision-making
- Conducting exploratory and descriptive analysis to inform strategic decisions
- Developing predictive models using programming languages such as R and MATLAB
- Utilizing TensorFlow and Scikit-Learn for deep learning and natural language processing tasks
- Collaborating with team members to adapt to varying client challenges and scopes
- Taking ownership of projects and consistently delivering quality work that drives client value
- Engaging in active listening and communication to appreciate diverse perspectives and needs
- Upholding professional and technical standards while adhering to the Firm's code of conduct
What You Must Have
- At least a Bachelor's degree
- At least 1 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Accounting, Analytics/Data Science, Artificial Intelligence/Robotics, Business Administration/Management, Computer Science/Information Systems, Cybersecurity, Engineering, Mathematics/Statistics, Operations/Supply Chain, Project/Technology Management, Risk Management/Insurance
- Demonstrating proficiency in data science algorithms and workflows
- Utilizing machine learning and deep learning techniques effectively
- Excelling in complex data analysis and predictive modeling
- Applying programming skills in MATLAB and R for data solutions
- Engaging in data-driven decision making and statistical analysis
- Leveraging experience with TensorFlow and Scikit-Learn libraries

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $50,500 - $140,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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