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Data Science Jobs in Virginia, MN (NOW HIRING)

Blueridgeinfotech

Data Engineer | Blueridge

Virginia, MN · On-site

$90 - $120/hr

Design, build, and maintain scalable data pipelines and architectures using various tools and ... Requires Bachelor's degree or foreign equivalent in Computer Science, Information Systems ...

New

Xpect-Solutions

Data Analytics Engineer

Virginia, MN · On-site

$90 - $130/hr

Job Overview XPECT Solutions is seeking a Data Analytics Engineerto support our Federal Government ... Bachelor's Degree in Computer Science or related field. Benefits Xpect Solutions, LLC is a one-of-a ...

New

Xpect Solutions

Data Analytics Engineer

Virginia, MN · On-site

$110 - $150/hr

Job Overview XPECT Solutions is seeking a Data Analytics Engineerto support our Federal Government ... Bachelor's Degree in Computer Science or related field. Benefits Xpect Solutions, LLC is a one-of-a ...

New

Xpect-Solutions

Data Engineer - Junior

Virginia, MN · On-site

$85 - $120/hr

Job Overview XPECT Solutions is seeking a Junior Data Engineerto support our Federal Government ... Bachelor's Degree in Computer Science or related field. Benefits Xpect Solutions, LLCis a one-of-a ...

New

Worky

Cloud/AI Engineer

Virginia, MN · On-site

$150 - $230/hr

We offer a broad range of technical expertise and experience in Digital Transformation, Data Management/Data Science, and Systems Modernization. At SIG, our people are our mission. Come join our team!

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Showing results 21-40

All JobsData Science JobsData Science Jobs in Virginia, MN

Data Science information

See Virginia, MN salary details

$36.1K

$118.1K

$189K

How much do data science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for data science in Virginia, MN is $118,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,700.00 and $130,800.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

What cities near Virginia, MN are hiring for Data Science jobs?

Cities near Virginia, MN with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Virginia, MN as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 18% Part Time, 1% Temporary, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $118,060 per year, or $56.8 per hour.

Data Analyst: Drive Insights & Data-Driven Solutions

Variyasinc

Virginia, MN • On-site

Other

Posted 16 days ago

Job description

Job Description:

As a Data Analyst you will analyze large sets of data to identify trends and insights and design and implement data-driven solutions for an organization.

Responsibilities:

  • Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software.
  • Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
  • Work with management to prioritize business and information needs.
  • Locate and define new process improvement opportunities.
  • Work with various Python Integrated Development Environments like Legoland, Machine learning platform and Databricks.
  • Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
  • Write new functions or applications in programming languages to conduct analyses.

Skills and Requirements:

  • Python, SQL, Google Cloud Platform Cloud, Pandas, Numpy, Pyspark, Power BI, data visualization tools, FLASK, DataBricks, NLP, Machine Learning, Data Mining, Statistical analysis and Data Modeling.
  • Work experience as a data analyst or in a related field.
  • Ability to work with stakeholders to assess potential risks.
  • Ability to analyze existing tools and databases and provide software solution recommendations.
  • Strong SQL or Excel skills, with aptitude for learning other analytics tools.

Education:

  • Bachelor’s degree in Computer Science or Business Analytics or Bachelor of Engineering in relevant skills.
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