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Data Science Jobs in La Crosse, WI (NOW HIRING)

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Quality Data Analyst

La Crosse, WI · On-site +1

S. in Food Science, Biology, Chemistry, Computer Science, Business, Statistics, or a related field. * Sharp critical thinking skills - you can validate information, spot bad data, and apply sound ...

Munich Re

Sr. Solution Architect

La Crosse, WI · On-site

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Fastenal Company

Supply Chain PT

Winona, MN · On-site

$15/hr

Math, Statistics, Data Science, Supply Chain, Operations, Finance or a related Business field ABOUT US: Since 1967 Fastenal has grown as a distributor of industrial and construction supplies from a ...

Fastenal Company

Supply Chain PT

Winona, MN · On-site

$15/hr

Math, Statistics, Data Science, Supply Chain, Operations, Finance or a related Business field ABOUT US: Since 1967 Fastenal has grown as a distributor of industrial and construction supplies from a ...

Fastenal Company

Supply Chain Specialist

Winona, MN · On-site

$42K - $70K/yr

... Data Science or a related Business field o Excellent written and oral communication skills o Proficient using Microsoft Office Suite o Demonstrate strong math aptitude, attention to detail and sense ...

Fastenal Company

Supply Chain Specialist

Winona, MN · On-site

$42K - $70K/yr

... Data Science or a related Business field o Excellent written and oral communication skills o Proficient using Microsoft Office Suite o Demonstrate strong math aptitude, attention to detail and sense ...

Fastenal Company

Inventory Liabilities Support

Winona, MN · On-site

$16/hr

... Data Science, Supply Chain, or other related education ABOUT US: Since 1967 Fastenal has grown as a distributor of industrial and construction supplies from a single branch to a Fortune 500 company ...

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All JobsData Science JobsData Science Jobs in La Crosse, WI

Data Science information

See La Crosse, WI salary details

$36.8K

$120.5K

$192.9K

How much do data science jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data science in La Crosse, WI is $120,495.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,700.00 and $133,500.00 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 are the most commonly searched types of Data Science jobs in La Crosse, WI?

The most popular types of Data Science jobs in La Crosse, WI are:

What job categories do people searching Data Science jobs in La Crosse, WI look for?

The top searched job categories for Data Science jobs in La Crosse, WI are:

What cities near La Crosse, WI are hiring for Data Science jobs?

Cities near La Crosse, WI with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in La Crosse, WI as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $120,495 per year, or $57.9 per hour.

Intern, Energy Data Science

Dairyland Power Cooperative

La Crosse, WI • On-site

$30/hr

Part-time

Posted 7 days ago

Job description

Hourley Wage: $30.00

PURPOSE: The Energy Data Science Intern will support strategic decision making by increasing data accessibility, performing statistical analysis, building predictive models, and providing actionable insights. This position advances all DPC's strategic priorities, but most notably our commitment to financial strength, growth & innovation, and our safety culture.

ESSENTIAL JOB FUNCTIONS:

Build, test and document data pipelines that ingest, transform and deliver data for analysis and reporting. Assist with integrating APIs, databases, enterprise applications and external data sources into Dairyland Power Cooperative's cloud-based Lakehouse environment. Clean, validate and organize energy and business data to improve reliability and accessibility. Perform statistical analysis to identify trends, quantify uncertainty and support business decisions. Develop and evaluate machine learning models for defined business applications. Support model deployment, validation, performance monitoring and ongoing improvement. Translate business questions into quantitative analyses. Present findings, assumptions and recommendations clearly to technical and nontechnical audiences. Create technical documentation for data sources, pipelines, models and analytical methods. Perform other duties as assigned.

MINIMUM QUALIFICATIONS:

Education & Experience: Currently pursuing either an undergraduate or graduate degree in data science, statistics, mathematics, artificial intelligence, computer science, or another related field.

Skills:

  • Experience using at least one scientific computing language, preferably Python

  • Foundational knowledge of data structures, statistical analysis and relational databases

  • Strong analytical, problem-solving and organizational skills

  • Strong verbal, written and interpersonal communication skills

  • Ability to work independently.

PREFERRED QUALIFICATIONS:

  • Experience with SQL and data modeling

  • Experience building data pipelines or integrating APIs

  • Familiarity with Microsoft Fabric, AWS or another cloud data platform

  • Familiarity with machine learning model development, validation, and deployment

  • Experience with Power BI or another data visualization tool

  • Experience using Git or another version control system

Licenses and Certifications:Valid Driver's License

Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms.

Environmental Demands: Normal work schedule is indoors.

Other Job Characteristics: Travel required, occasionally overnight. Works with limited supervision in a variably paced, variable pressure setting. Handles multiple priorities.

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