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Data Science Jobs in Buffalo, MN (NOW HIRING)

Trelleborg

Director of Data Analytics and AI

Plymouth, MN · On-site

$160K - $205K/hr

Degree in Computer Science, Data Science, Information Management, or related field * 10+ years of relevant experience in data, analytics, or digital leadership roles * Proven experience in data ...

Abbott

OpEx Data Analyst I

Plymouth, MN

OpEx Data Analyst Working at Abbott At Abbott, you can do work that matters, grow, and learn, care ... Computer Science, AI, software engineering or disciplines including Databases, Mathematics ...

Abbott

OpEx Data Analyst I

Plymouth, MN · On-site

OpEx Data Analyst Working at Abbott At Abbott, you can do work that matters, grow, and learn, care ... Computer Science, AI, software engineering or disciplines including Databases, Mathematics ...

Abbott

OpEx Data Analyst I

Plymouth, MN · On-site

OpEx Data Analyst Working at Abbott At Abbott, you can do work that matters, grow, and learn, care ... Computer Science, AI, software engineering or disciplines including Databases, Mathematics ...

UnitedHealth Group

Data Analyst - Remote

Minnetonka, MN · On-site +1

... data science) analysis; and/or image or unstructured data analysis using sophisticated theoretical frameworks You'll be rewarded and recognized for your performance in an environment that will ...

Target

Data Engineer - Finance AI Solutions

Minneapolis, MN · On-site +1

$75K - $135K/yr

Join our global in-house technology team of more than 5,000 engineers, data scientists, architects, and product managers who are striving to make Target the most convenient, safe, and joyful place to ...

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All JobsData Science JobsData Science Jobs in Buffalo, MN

Data Science information

See Buffalo, MN salary details

$39.5K

$129.2K

$206.9K

How much do data science jobs pay per year?

As of Aug 18, 2026, the average yearly pay for data science in Buffalo, MN is $129,218.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,700.00 and $143,200.00 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 popular job titles related to Data Science jobs in Buffalo, MN?

For Data Science jobs in Buffalo, MN, the most frequently searched job titles are:

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

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

Data Science jobs near you
Infographic showing various Data Science job openings in Buffalo, MN as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,218 per year, or $62.1 per hour.

Director of Data Analytics and AI

Trelleborg

Plymouth, MN • On-site

$160K - $205K/hr

Full-time

Re-posted 6 days ago

Trelleborg rating

8.2

Company rating: 8.2 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

89th of 540 rated manufacturers

Job description

Tasks and Responsibilities

  • Develop and execute enterprise-wide data, digital, and AI strategy
  • Establish and enforce data governance policies, standards, and frameworks
  • Design and implement master data architecture, models, and hierarchies
  • Ensure master data accuracy and consistency across customer, product, vendor, and operational domains
  • Define and manage processes for creation and maintenance of master data
  • Lead digital transformation initiatives including AI, analytics, and data platforms
  • Identify opportunities for AI-driven optimization in operations and decision-making
  • Develop reporting standards, dashboards, and advanced analytics capabilities
  • Monitor emerging technologies and implement innovative digital solutions
  • Establish AI governance including model lifecycle and risk management
  • Lead, develop, and mentor global data and AI teams
  • Collaborate with cross-functional stakeholders to align initiatives with business priorities
  • Manage Data & AI budget and ensure cost efficiency and ROI
  • Conduct data quality reviews, audits, and continuous improvement initiatives

Education and Experience

  • Degree in Computer Science, Data Science, Information Management, or related field
  • 10+ years of relevant experience in data, analytics, or digital leadership roles
  • Proven experience in data governance and master data management
  • Strong experience in enterprise data architecture and analytics platforms
  • Experience leading digital transformation and AI initiatives
  • Experience in global / multi-site environments
  • Knowledge of data privacy regulations (e.g., GDPR, ITAR)
  • Fluent English (spoken and written)

Competencies

  • Strategic thinking and strong business acumen
  • Leadership and team development capability
  • Strong communication and stakeholder management skills
  • Advanced analytical and problem-solving skills
  • Ability to interpret complex data and drive insights
  • Financial and budget management capability
  • Strong execution and results orientation

Key Performance Indicators

  • Data quality and master data accuracy
  • Adoption of governance frameworks
  • ROI of Data & AI initiatives
  • Improvement in reporting efficiency and time-to-insight
  • Adoption of analytics tools
  • Stakeholder satisfaction

Travel required during key transformation phases, domestic and international (estimated <20%)

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