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Entry Level Machine Learning Jobs in Plymouth, MN

Aerotek

Machine Operator

Minneapolis, MN

$18/hr

Machine Operator - Entry Level | Full Training Provided Start your manufacturing career in a clean ... If you enjoy learning, staying active, and being part of a dependable team, this is a great place ...

Pwc

AI & GenAI Data Scientist - Manager

Minneapolis, MN

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Machine Learning information

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How much do entry level machine learning jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for entry level machine learning in Plymouth, MN is $18.43, according to ZipRecruiter salary data. Most workers in this role earn between $16.49 and $20.05 per hour, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
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Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Plymouth, MN as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $38,341 per year, or $18.4 per hour.

GenAI Python Systems Engineer - Experienced Associate

Pwc

Minneapolis, MN

$63K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 13 hours ago

PwC rating

8.3

Company rating: 8.3 out of 10

Based on 77 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants

Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Associate

Job Description & Summary

The Opportunity
As a GenAI Python Systems Engineer - Experienced Associate, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients, transforming raw data into actionable insights that drive business growth. Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale, enabling informed decision-making and innovation.
As an Associate, you will focus on learning and contributing to client engagements while developing your skills and knowledge to deliver quality work. You will adapt to working with a variety of clients and team members, each presenting unique challenges and opportunities for growth. You are expected to take ownership and consistently deliver work that drives value for our clients and success as a team, building a personal brand and opening doors to more opportunities.
In this role at PwC, you will engage in designing AI systems, data wrangling, and software implementation to enable scalable AI models. You will be part of a fast-paced environment, where every experience is an opportunity to learn and grow, contributing to the firm's success and your professional development.
Responsibilities
- Designing and implementing AI systems using Python and machine learning libraries such as Scikit-Learn
- Developing data pipelines and models to transform raw data into actionable insights for clients
- Collaborating with team members to support AI-driven automation and cognitive solutions
- Conducting complex data analysis to discern patterns and inform decision-making
- Applying programming languages to build scalable AI and machine learning solutions
- Confirming data quality and integrity throughout the development process
- Engaging in active listening and accepting feedback to enhance personal growth and team performance
- Building commercial awareness by understanding how the business works and its impact on client solutions
- Upholding professional and technical standards, including the Firm's code of conduct and independence requirements
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: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in Python and Scikit-Learn for machine learning
- Utilizing AI implementation skills in client-facing projects
- Engaging in complex data analysis and data modeling
- Applying machine learning libraries to enhance data-driven solutions
- Adapting to fast-paced environments with diverse client needs

Travel Requirements

Up to 80%

Job Posting End Date

The salary range for this position is: $63,000 - $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

What PwC employees say

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Benefits

Hours and flexibility

Workplace

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About pwc

Sourced by ZipRecruiter

We know that the future success of our firm is contingent on equitable experiences for our people. From recruitment to partnership, we’re working hard to give every person an equitable opportunity to grow and to thrive as part of our community of solvers. We understand that establishing and maintaining a fair, equitable and welcoming environment for all people requires building a culture of belonging: a shift from awareness to empathy — while demonstrating inclusive leadership that cultivates trust among our people and our clients. PwC is committed to advancing diversity, equity and inclusion (DEI) through an evidence-based strategy designed to achieve well-defined and meaningful aspirational goals. Our aim is to solve problems for the long term, as that is how we build trust and continue to build on our culture of belonging. At the core of this endeavor are stated goals and a series of linked programs enabling targeted interventions at key moments in our employees’ career trajectories.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

London, London, UK

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