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Data Scientist Machine Learning Jobs in Minnesota

On-Demand Group

Sr. Data Scientist

Minneapolis, MN · On-site

Evaluate and recommend appropriate machine learning algorithms and modeling techniques * Monitor ... Mentor junior and mid-level Data Scientists through technical guidance, code reviews, and ...

Jobtailor

Senior Data Scientist

Minneapolis, MN · On-site

$120 - $180/hr

Expertise in data science, machine learning, data mining, operations research, and statistical modeling techniques, specifically for high-volume and complex datasets. * Knowledge of best coding ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

System One

Data Scientist

Minneapolis, MN · On-site

System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between ...

Dlapiper

Data Scientist

Minneapolis, MN · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred. Must be self-driven, curious and creative. * Experience must include creating and using ...

Accelint

Data Scientist

Saint Paul, MN · On-site

$105K - $126K/yr

The Data Scientist will apply knowledge of statistics, machine learning, programming, and data modeling. They use a flexible, analytical approach to design, develop, and evaluate predictive models ...

Accelint Holdings LLC

Data Scientist

Saint Paul, MN · On-site

$106 - $127/hr

The Data Scientist will apply knowledge of statistics, machine learning, programming, and data modeling. They use a flexible, analytical approach to design, develop, and evaluate predictive models ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Minnesota

Data Scientist Machine Learning information

See Minnesota salary details

$36.7K

$120.2K

$192.5K

How much do data scientist machine learning jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data scientist machine learning in Minnesota is $120,211.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,500.00 and $133,200.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What is the salary of data scientist in machine learning?

The salary of a data scientist specializing in machine learning typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in programming, statistical analysis, and tools like Python or TensorFlow may earn higher compensation.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Minnesota?

The most popular types of Data Scientist Machine Learning jobs in Minnesota are:

What are popular job titles related to Data Scientist Machine Learning jobs in Minnesota?

For Data Scientist Machine Learning jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Data Scientist Machine Learning jobs in Minnesota look for?

The top searched job categories for Data Scientist Machine Learning jobs in Minnesota are:

Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 9% Part Time, and 6% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $120,211 per year, or $57.8 per hour.

Sr. Data Scientist

On-Demand Group

Minneapolis, MN • On-site

Other

Posted 14 days ago

Job description

About the Role

We are seeking an experienced Senior Data Scientist to join a collaborative, fast-paced data science team focused on delivering measurable business value through machine learning. This is a hands-on technical role for someone who enjoys solving complex business problems, mentoring teammates, and driving continuous improvement across an established portfolio of production models.

Unlike organizations focused primarily on research or greenfield development, our team spends the majority of its time optimizing, enhancing, and scaling existing machine learning solutions. You''''''''ll partner closely with data engineers, business stakeholders, and fellow data scientists to improve model performance, identify new opportunities, and help shape the future direction of our data science practice.

The team operates in an agile, CI/CD environment with bi-weekly releases, making collaboration, iterative delivery, and continuous improvement essential to success.

Key Responsibilities
  • Lead the enhancement, tuning, retraining, and optimization of production machine learning models
  • Design and implement advanced modeling solutions to solve complex business challenges
  • Evaluate and recommend appropriate machine learning algorithms and modeling techniques
  • Monitor model performance and identify opportunities to improve accuracy, scalability, and business impact
  • Partner closely with Data Engineers to support data pipelines, feature engineering, and model deployment
  • Build and maintain datasets using SQL and Python
  • Develop and maintain work within Jupyter Notebooks in a cloud-based environment
  • Lead model lifecycle activities, including testing, validation, deployment, and ongoing monitoring
  • Mentor junior and mid-level Data Scientists through technical guidance, code reviews, and collaborative problem solving
  • Partner with business stakeholders to translate business objectives into scalable analytical solutions
  • Communicate technical concepts, recommendations, and results clearly to both technical and executive audiences
  • Contribute to improving team standards, best practices, and machine learning processes
Required Qualifications
  • 5+ years of experience in Data Science, Machine Learning, or Applied Analytics
  • Expert-level proficiency with Python and SQL
  • Extensive experience working in Jupyter Notebooks, preferably in a cloud environment
  • Proven experience developing, deploying, monitoring, and maintaining production machine learning models
  • Strong understanding of:
    • Machine learning model selection and evaluation
    • Model monitoring, drift detection, and performance optimization
    • Development versus production environments
    • Data pipelines and feature engineering
    • Model lifecycle management
  • Experience leading or mentoring other Data Scientists
  • Strong problem-solving and analytical skills
  • Ability to work independently while collaborating effectively across cross-functional teams
  • Excellent verbal and written communication skills with both technical and non-technical audiences
Preferred Qualifications
  • Experience with Snowflake
  • Experience supporting customer-facing machine learning applications
  • Experience with personalization or recommendation engines
  • Experience with customer lifecycle modeling, including churn prediction, propensity modeling, customer lifetime value (CLV), and segmentation
  • Experience working in CI/CD and agile software development environments
  • Experience collaborating closely with Data Engineering, Product, and business stakeholders
  • Experience helping establish technical standards or best practices for Data Science teams
What We''''''''re Looking For
  • A hands-on technical leader who enjoys building alongside the team
  • A collaborative mentor who helps elevate those around them
  • A versatile Data Scientist with broad modeling experience across multiple problem domains rather than deep specialization in a single technique
  • Someone who takes ownership, drives outcomes, and proactively identifies opportunities for improvement
  • A practical, business-minded problem solver who balances technical excellence with delivering measurable value
  • Comfortable working in a fast-paced, iterative environment with frequent releases and changing priorities
  • A team player who enjoys wearing multiple hats and contributing wherever needed
Work Environment
  • Hybrid work environment with approximately three days per week onsite
  • Agile team operating in two-week sprints
  • Highly collaborative culture with close partnership between Data Science, Data Engineering, and business stakeholders
  • Continuous learning environment where contractors are treated as integral members of the team and encouraged to contribute ideas and influence technical direction

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