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Data Science Jobs in Austin, MN (NOW HIRING)

University of Minnesota

Post-Doctoral Associate

Austin, MN · Hybrid

$62K - $75K/mo

Compile and analyze processed data using a variety of software tools. Science communications - 5% Communicate research findings to different audiences, including the PI and group members, the broader ...

WM

Gas Operations Supervisor

Lake Mills, IA · On-site

On a routine basis, collect and manage data entry from wellfield extraction and environmental ... Bachelor's degree in Environmental Science, Physical Science, Biology, or Chemistry (or related ...

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$36.5K

$119.5K

$191.3K

How much do data science jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data science in Austin, MN is $119,513.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,900.00 and $132,400.00 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 Austin, MN are hiring for Data Science jobs?

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

Data Science jobs near you
Infographic showing various Data Science job openings in Austin, MN as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $119,513 per year, or $57.5 per hour.

Senior Data Engineer - Corporate Office (Austin, MN preferred)

Columbus Craft Meats

Austin, MN

$103K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago

Job description

SENIOR DATA ENGINEER - CORPORATE OFFICE (AUSTIN, MN PREFERRED)  

HORMEL FOODS CORPORATION

To save time applying, Hormel Foods does not offer sponsorship of job applicants for employment-based visas for this position at this time. 

ABOUT HORMEL FOODS 

Hormel Foods Corporation, based in Austin, Minnesota, is a global branded food company with approximately $12 billion in annual revenue across more than 80 countries worldwide. Its brands includePlanters, Skippy,SPAM,HormelNatural Choice, Applegate, Wholly, HormelBlack Label, Columbus, Jennie-O and more than 30 other beloved brands. The company is a member of the S&P 500 Index and the S&P 500 Dividend Aristocrats, was named one of the best companies to work for by U.S. News & World Report, one of America's most responsible companies by Newsweek, recognized by TIME magazine as one of the World's Best Companies, and has received numerous other awards and accolades for its corporate responsibility and community service efforts. For more information, visitwww.hormelfoods.com. 

SUMMARY:

As a Senior Data Engineer, you will lead the Supply Chain Data Engineering team responsible for delivering curated data assets, data pipelines, dimensional models, semantic models, and foundational data capabilities that support planning, procurement, manufacturing, inventory, logistics, and transportation across Hormel Foods. 

This role plays a key part in advancing our Enterprise Data Foundation by leveraging technologies Google Cloud Platform (GCP), BigQuery, Composer (Airflow), enterprise Python-based ingestion and orchestration capabilities, Incorta, and enterprise semantic layer technologies. This role will help bridge Hormel's modern cloud data ecosystem and legacy enterprise data platforms while delivering trusted data assets that power Supply Chain analytics and decision-making. 
  

RESPONSIBILITIES: 

  • Lead and develop the Supply Chain Data Engineering team responsible for delivering curated data assets, data pipelines, dimensional models, semantic models, and foundational data capabilities supporting planning, procurement, manufacturing, inventory, logistics, and transportation. Utilize enterprise ingestion, orchestration, and platform capabilities to acquire, integrate, transform, and curate data that supports analytics, reporting, and business decision-making.
  • Partner with Supply Chain stakeholders, Data Products & Solutions teams, architects, data scientists, and application teams to prioritize initiatives and deliver scalable data solutions that support business objectives.
  • Design, develop, and support Supply Chain data solutions across modern and legacy platforms, including BigQuery, Composer (Airflow), Python, Incorta, Oracle Analytics Server (OAS), Oracle Enterprise Data Warehouse, Informatica, PL/SQL, and enterprise semantic layer technologies.
  • Establish and promote engineering best practices, including data modeling standards, code reviews, testing strategies, CI/CD adoption, monitoring, observability, and operational support processes.
  • Partner with Data Governance teams and business data stewards to implement and maintain data quality rules, metadata cataloging, business glossary definitions, critical data elements, observability capabilities, and data remediation processes across Supply Chain data domains.
  • Drive modernization initiatives that advance the Enterprise Data Foundation, improving scalability, reliability, developer productivity, and long-term maintainability while reducing technical debt.
  • Provide technical leadership through architecture reviews, design reviews, mentoring, coaching, and cross-functional collaboration with Data Platform Engineering, Architecture, Infrastructure, Security, Governance, and Integration teams.

QUALIFICATIONS:

Required

  • Bachelor's degree in computer science, MIS, engineering, mathematics, or related field, and significant experience supporting enterprise data, analytics, and technology platforms. 
  • 7+ years of experience developing and optimizing SQL solutions.
  • 7+ years of experience designing, implementing, and supporting enterprise data warehouse, lakehouse, or modern data platform solutions. 
  • 5+ years of experience developing data pipelines and data integration solutions using Python and/or modern ETL/ELT technologies.
  • Strong experience with dimensional modeling, semantic modeling, and curated analytical data structures, including development and support of enterprise semantic layer solutions. 
  • Demonstrated leadership experience leading technical teams, mentoring engineers, and delivering cross-functional initiatives. 
  • Experience partnering with business stakeholders to translate business requirements into scalable data solutions.
  • Strong understanding of Supply Chain business processes including planning, procurement, manufacturing, inventory management, logistics, transportation, or warehouse operations. 
  • Experience implementing data quality, monitoring, observability, and operational support practices.
  • Excellent communication, organizational, problem-solving, and stakeholder management skills. 
  • Applicants must not now, or at any time in the future, require employer sponsorship for a work visa. 
  • Applicants must be authorized to work in the United States for any employer. 


Preferred

  • Experience with Google Cloud Platform technologies including BigQuery, Cloud Storage (GCS), Composer (Airflow), Dataflow, Pub/Sub, and Data Fusion.
  • Experience utilizing enterprise ingestion and orchestration frameworks to acquire, process, and curate enterprise data assets.
  • Experience developing enterprise-scale data pipelines and data integration solutions using Python.
  • Experience with Incorta analytics and data platform technologies.
  • Experience designing and implementing semantic layer solutions utilizing technologies such as AtScale, Cube, Oracle Analytics Server (OAS), or similar platforms.
  • Experience designing and supporting curated data products for enterprise analytics and self-service reporting. 
  • Experience with Oracle Enterprise Data Warehouse environments.
  • Experience with Informatica ETL development.
  • Advanced SQL and PL/SQL development, performance tuning, and optimization experience.
  • Experience partnering with Data Governance teams and business data stewards on metadata management, business glossary development, data quality initiatives, observability, critical data elements, and remediation processes.
  • Experience supporting enterprise data modernization initiatives spanning both cloud-native and legacy data ecosystems.
  • Experience within food manufacturing, consumer packaged goods (CPG), Supply Chain, logistics, or related industries.
  • Experience managing and developing technical teams.

LOCATION: Corporate Office Austin, MN preferred; Eden Prairie Sales Office, Eden Prairie MN   

A comprehensive relocation package to the above areas will be offered, if required.  

At Hormel Foods, base pay is one part of our total compensation package and is determined within a range. The base hiring pay range for the Senior Data Engineer role is between $119,525 - $167,325 per year, and your actual base pay within that range will depend upon a variety of factors including, but not limited to, job-related knowledge, skill set, level of experience, and geographic market location.

BENEFITS: Other components of Hormel Foods' total compensation package includes comprehensive medical, dental and vision coverage, discretionary annual merit increases, bonuses and profit sharing, 401(k) with employer match, stock purchase plan, paid time off, free two-year community/technical college tuition for children of employees, and more.

TRAVEL REQUIREMENTS: 10% of the time 

For immediate consideration, apply online at: www.hormelfoods.com/careers

At Hormel we invite difference and diversity in all aspects.  We offer a space of support, understanding, and community.  We are committed to the journey!  Learn more about our progress here: https://www.hormelfoods.com/about/inclusion-and-belonging/

Hormel Foods provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.

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