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Entry Level Machine Learning Jobs in Minnesota (NOW HIRING)

Douglas Machine, Inc.

Plater - Day Shift

Alexandria, MN · On-site

$17 - $19/hr

Description Looking for an entry-level opportunity at a fast-paced, growing company? Join the ... Learning racking techniques that optimize part quality and quantity * Building racks to optimize ...

Douglas Machine, Inc.

Plater

Alexandria, MN · On-site

$17 - $19/hr

Description Looking for an entry-level opportunity at a fast-paced, growing company? Join the ... Learning racking techniques that optimize part quality and quantity * Building racks to optimize ...

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All JobsEntry Level Machine Learning JobsEntry Level Machine Learning Jobs in Minnesota

Entry Level Machine Learning information

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$12

$17

$21

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

As of Jun 30, 2026, the average hourly pay for entry level machine learning in Minnesota is $17.11, according to ZipRecruiter salary data. Most workers in this role earn between $15.29 and $18.61 per hour, depending on experience, location, and employer.

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 is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often found in large tech companies or specialized firms. These positions usually require extensive experience, advanced skills in deep learning, data science, and proficiency with tools like TensorFlow or PyTorch, along with leadership responsibilities and sometimes equity or bonuses. Such salaries are rare and generally reflect seniority, expertise, and the strategic importance of AI initiatives within organizations.

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.

Which 3 jobs will survive AI?

Entry level machine learning roles are likely to persist as they require specialized skills in data analysis, programming, and understanding complex algorithms. Jobs that involve creative thinking, emotional intelligence, or physical tasks, such as data scientists, AI specialists, and software engineers, are expected to remain in demand despite AI advancements.

How to get into machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, mathematics, and data analysis. Gaining skills through online courses, tutorials, and practicing with projects using tools like Python and libraries such as scikit-learn or TensorFlow can help build a portfolio. Earning certifications or completing relevant coursework can also improve job prospects for beginners.

What are entry level machine learning jobs?

Entry level machine learning jobs are positions designed for individuals just starting their careers in the field of machine learning. These roles typically involve working on data preparation, building and testing basic models, and assisting senior data scientists or engineers. Common job titles include Machine Learning Engineer, Data Analyst, or Junior Data Scientist. Requirements often include proficiency in programming languages such as Python, foundational knowledge of statistics, and experience with machine learning libraries. These jobs provide hands-on experience and mentorship to help new professionals grow their skills.

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 engineers make $500,000?

Senior engineers in fields like software, electrical, or aerospace engineering can reach or exceed $500,000 annually, especially with experience, specialized skills, and leadership roles. High-paying positions often require advanced expertise, certifications, and work in competitive industries or companies with lucrative compensation packages.
More about Entry Level Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Minnesota? The most popular types of Machine Learning jobs in Minnesota are:
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What job categories do people searching Entry Level Machine Learning jobs in Minnesota look for? The top searched job categories for Entry Level Machine Learning jobs in Minnesota are:
What cities in Minnesota are hiring for Entry Level Machine Learning jobs? Cities in Minnesota with the most Entry Level Machine Learning job openings:
Entry Level Machine Learning jobs near you
Utility Data and Modeling Analyst

Utility Data and Modeling Analyst

HDR

Saint Louis Park, MN • On-site

Full-time

Posted 7 days ago

Key responsibilities

  • Assist with building and maintaining hydraulic model data for water distribution and wastewater collection systems using GIS datasets, as-built drawings, and field data.

  • Perform data acquisition, cleaning, validation, exploratory analysis, and develop analytical and visualization outputs to support technical evaluations.

  • Contribute to asset inventory development, condition assessment processes, and risk prioritization activities supporting water and wastewater capital planning.

HDR rating

9.1

Company rating: 9.1 out of 10

Based on 55 frontline employees who took The Breakroom Quiz

20th of 357 rated engineering

Job description

At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we foster a culture of inclusion throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world?
Watch Our Story:' https://www.hdrinc.com/our-story'
Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.
We believe water is more than a resource, it's a shared responsibility. As part of our Water Business Group, you'll help shape how communities manage water for generations to come. From delivering safe drinking water and treating wastewater responsibly to developing sustainable water supplies and protecting lives and property through flood control, your work will directly support public health, environmental sustainability, and infrastructure resilience. We bring together experts across disciplines to solve complex challenges with bold thinking and technical excellence. Whether you're modernizing aging systems or pioneering innovative approaches, your contributions will make a meaningful difference in people's lives. This isn't just a job, it's a chance to lead change, drive progress, and leave a lasting legacy.
About the Role
HDR is seeking an entry-level Utility Data, Asset Management & Hydraulic Modeling Analyst to support water and wastewater utility projects through applied hydraulic modeling analysis, data analytics, GIS, and asset management. This position contributes to system evaluations, capital planning, regulatory analysis, and development of technical deliverables for municipal utility clients. The successful candidate will demonstrate strong analytical capability, technical rigor, and an interest in advancing data-driven utility planning.
Key Responsibilities:
Hydraulic Modeling & System Analysis
  • Assist with building and maintaining hydraulic model data for water distribution and wastewater collection systems using GIS datasets, as-built drawings, and field data.
  • Support hydraulic simulations, system performance evaluations, and scenario analyses for planning studies and operational assessments.
  • Utilize data from industry modeling tools such as InfoWater, InfoSewer, InfoSWMM, InfoWorks ICM, SewerGEMs, WaterGEMs, EPANet, and ArcGIS Pro.

Data Engineering, Analytics & Visualization
  • Perform data acquisition, cleaning, validation, and exploratory analysis on large datasets including SCADA data, metering data, GIS layers, and monitoring records.
  • Develop analytical and visualization outputs using SQL, Power BI, Python, R, and GIS platforms to support technical evaluations.
  • Support database management, data structuring, and creation of modeling-ready datasets to improve study reliability and documentation.
  • Handle highly sensitive and confidential information with professionalism and discretion
  • Collaborate with stakeholders to improve business decisions by identifying patterns and trends in data
  • Develop data products including reports, visualizations, and dashboards
  • Adhere to software and data science development standards
  • Perform data acquisition, sourcing, cleaning and exploratory data analysis (EDA)
  • Transform raw data into usable attributes for machine learning modules through feature engineering
  • Manage model lifecycle including development, deployment, data drift detection, model retraining, and model inference.
  • Create automated data pipelines and data engineering solutions
  • Develop advanced and custom predictive models (classification, regression, time series, neural networks, natural language processing, and computer vision)
  • Tune models with training, hyperparameters with comprehensive validation and testing processes

Asset Management & Capital Planning
  • Contribute to asset inventory development, condition assessment processes, and risk prioritization activities supporting water and wastewater capital planning.
  • Assist in preparing asset management and capital improvement plan documents, including risk modeling graphics, lifecycle analysis summaries, and decision-support exhibits.
  • Integrate asset, condition, and geospatial data to support long-term strategic planning for utility infrastructure.

Utility Planning, Policy Analysis & Technical Reporting
  • Support development of technical reports, planning documents, regulatory analyses, and client presentations.
  • Assist with evaluating impacts of evolving state and federal environmental policies on client utility systems.
  • Leverage predictive models to optimize business results
  • Contribute to studies involving financial planning, rate evaluation, and long-range system needs assessment.

Professional Collaboration
  • Actively participate in HDR's employee-owned, collaborative culture by working closely with multidisciplinary teams including engineers, planners, analysts, and project managers.
  • Communicate findings through written reports, visualizations, engineering graphics, and presentations.
  • Maintain high standards of quality control, documentation, and analytical accuracy.

Preferred Qualifications
  • Bachelor's Degree
  • A minimum of 3 years experience in a data science role
  • Foundational knowledge or academic experience in hydraulics, environmental systems, data analytics, GIS, or related disciplines.
  • Familiarity with or academic exposure to hydraulic modeling concepts or tools.
  • Experience with ArcGIS Desktop, ArcGIS Pro, or ArcGIS Online.
  • Oracle Spatial or SQL Server Spatial back-end data processing experience
  • Understanding of asset management principles such as condition assessment, risk scoring, or lifecycle planning.
  • Interest in environmental regulations and policy frameworks related to water and wastewater utilities.

#LI-EV1
Qualifications
Required Qualifications
  • A degree in a closely related field or combination of education and relevant experience
  • A minimum of 3 years experience with data engineering tools and languages such as SQL, Power Query, and Pandas
  • A minimum of 3 years experience with business intelligence tools such as Power BI, Tableau, Plotly, Seaborn, and Matplotlib
  • A minimum of 3 years experience with data science languages such as Python and R
  • Self-motivated, detail-oriented professional, ability to multitask a must
  • Proficiency with MS Office including Word and Outlook
  • Ability to handle confidential information
  • Excellent writing and people skills
  • Strong math and organizational skills
  • Flexibility and ability to prioritize and handle multiple tasks and various managers in a fast-paced environment
  • Excellent verbal and written communication skills including grammar, punctuation, proofreading, spelling and telephone skills
  • An attitude and commitment to being an active participant of our employee-owned culture is a must
  • In-depth knowledge of machine learning algorithms, statistical models, and data analytics
  • Experience completing multiple data science projects

What We Believe
HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve.
Our Commitment
As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day.
Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees.

What HDR employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

HDR logo

About HDR

Sourced by ZipRecruiter

At HDR, we specialize in engineering, architecture, environmental and construction services. While we are most well-known for adding beauty and structure to communities through high-performance buildings and smart infrastructure, we provide much more than that. We create an unshakable foundation for progress because our multidisciplinary teams also include scientists, economists, builders, analysts and artists.

Industry

Specialized design services

Company size

5,001 - 10,000 Employees

Headquarters location

Omaha, NE, US

Year founded

1917

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