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Associate Data Science Analyst Jobs in Minnesota

Elder Research Inc.

Data Scientist

Virginia, MN · On-site

Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences. * Proficiency in Python, including ...

Xcel Energy

Data Science Intern CO, MN

Minneapolis, MN · On-site

$22.10 - $27.90/hr

A Data Science Intern will play a crucial role in handling and analyzing large datasets to uncover valuable insights. They utilize statistical methods, machine learning algorithms, and data ...

Horizontal Talent

Data Intelligence Analyst

Eagan, MN · On-site +1

$22 - $46/hr

Skills * Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Information Systems, or a related field. * At least 7 years of experience in data analytics, business ...

Omm IT Solutions

Data Product Manager

Saint Paul, MN · On-site

Partnering closely with data engineering, data science, analytics, and business policy and administration, the Data Product Manager will facilitate and help drive the path towards trusted, reusable ...

On-Demand Group

Sr. Data Scientist

Minneapolis, MN · On-site

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

Polaris, Inc.

Data Scientist

Plymouth, MN · On-site

$87K - $115K/yr

Gather feedback from business users to continuously improve data science products. Desired Competencies: * Critical Thinking: You analyze information objectively, evaluate options, and apply sound ...

Omm IT Solutions

Data Product Manager

Saint Paul, MN · On-site

Partnering closely with data engineering, data science, analytics, and business policy and administration, the Data Product Manager will facilitate and help drive the path towards trusted, reusable ...

Polaris, Inc.

Data Scientist

Plymouth, MN · On-site

$87K - $115K/yr

Gather feedback from business users to continuously improve data science products. Desired Competencies: * Critical Thinking: You analyze information objectively, evaluate options, and apply sound ...

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All JobsAssociate Data Science Analyst JobsAssociate Data Science Analyst Jobs in Minnesota

Associate Data Science Analyst information

What does an associate data science analyst do?

An Associate Data Science Analyst is an entry-level professional who assists in collecting, analyzing, and interpreting data to help organizations make data-driven decisions. They work closely with senior data scientists and analysts, using statistical tools and programming languages like Python or R to process data, create reports, and visualize results. Their responsibilities often include cleaning and organizing data sets, performing exploratory data analysis, and supporting the development of predictive models. This role is a great way to gain hands-on experience in data science while building foundational skills for more advanced positions.

What are the key skills and qualifications needed to thrive as an associate data science analyst, and why are they important?

To thrive as an Associate Data Science Analyst, you need a solid grounding in statistics, data analysis, and programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with data visualization tools like Tableau, SQL databases, and potentially foundational certifications in data analytics are commonly required. Strong problem-solving, critical thinking, and effective communication skills help analysts interpret data insights and convey findings to stakeholders. These competencies are crucial for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

What types of projects and datasets do associate data science analysts typically work with, and how do they contribute to larger team goals?

Associate Data Science Analysts often work on projects involving data cleaning, exploratory analysis, and basic model development using real-world datasets such as sales figures, customer behavior logs, or operational metrics. Their primary responsibility is to prepare, analyze, and visualize data to uncover insights that support business decisions. They collaborate closely with more senior data scientists, business analysts, and stakeholders to ensure that their analyses align with organizational objectives. This role provides valuable exposure to the end-to-end data science workflow and lays the foundation for advancement into more specialized or senior data science positions.

What is the difference between Associate Data Science Analyst vs Data Analyst?

AspectAssociate Data Science AnalystData Analyst
Required CredentialsBachelor's degree in data-related field; some roles prefer certifications in data analysis or programmingBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Excel or SQL are common
Work EnvironmentCollaborates with data scientists and engineers; involved in data modeling and analysis tasksFocuses on data collection, cleaning, and reporting; often works with business teams
Employer & Industry UsageUsed in tech, finance, healthcare industries; entry-level role in data teamsWidely used across industries for business insights and reporting

The Associate Data Science Analyst and Data Analyst roles share similarities in educational background and industry usage. However, the Associate Data Science Analyst typically involves more technical tasks like data modeling and working closely with data science teams, whereas Data Analysts focus more on data reporting and business insights. Both roles serve as entry points into data careers but differ in technical depth and collaboration scope.

What can I do with an associate data science analyst's degree in data science?

An associate data science analyst's degree prepares individuals for entry-level roles such as data analyst, data technician, or business intelligence assistant. These roles involve collecting, cleaning, and analyzing data using tools like Excel, SQL, and basic programming languages such as Python or R. The degree provides foundational skills for working in data-driven environments and can lead to further specialization or advancement in data science careers.

What are the most commonly searched types of Data Science Analyst jobs in Minnesota?

The most popular types of Data Science Analyst jobs in Minnesota are:

Associate Data Science Analyst jobs near you
Infographic showing various Associate Data Science Analyst job openings in Minnesota as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Data Scientist

Virginia, MN • On-site

Elder Research Inc.
Computing Infrastructure Providers, Data Processing, Web Hosting • 51 - 200 employees
Learn more about Elder Research Inc.external

Other

Re-posted 9 days ago

Key responsibilities

  • Lead the development, training, and maintenance of predictive models using advanced analytical methods such as time series forecasting and NLP.

  • Engage in requirements gathering and data analysis to connect business use cases with underlying data patterns, and define solutions for ambiguous problems.

  • Utilize data engineering skills to integrate, deploy, and troubleshoot analytical solutions, ensuring scalability and operational reliability.

Job description

Career Opportunities with Elder Research

A great place to work.

Locations: USA-VA-Arlington OR USA-NC-Raleigh

Posting Date: 06/12/2026

Security Clearance Required: NONE

Remote Type: Hybrid

Time Type: Full time

Data Scientist - Hybrid (Raleigh, NC or Washington DC)

Elder Research Inc., a wholly owned subsidiary of MANTECH International Corporation, seeks a motivated, career and customer-oriented Data Scientist to join our team in Raleigh, NC or Washington DC. This role is hybrid, and candidates must be located in the Raleigh or Washington, DC market to support 1–2 days onsite per week.

This role is for a highly experienced and curious data scientist to lead the full-lifecycle development and deployment of analytical solutions at Elder. You will operate as a critical member of an analytics team, acting as a trusted advisor to diverse client partner team. The focus is on leveraging advanced analytical methods to turn ambiguous business challenges into high-impact, production-ready models, supported by robust data engineering practices.

Responsibilities
  • Lead Data Science Initiatives: Dive deep into complex and often nebulous requirements, applying expertise in areas such as time series forecasting and Natural Language Processing (NLP) to build, train, and maintain predictive models. Additionally, candidate should be capable of leading and mentoring more junior data scientists.
  • Problem Solver and Consultant: Engage in critical requirements gathering and data "sleuthing" (approximately 10-20% of the role) to connect business use cases with underlying data patterns. You will carve your own path to define and solve problems that lack clear initial definitions.
  • Deliver Automation and Insights: Partner with technical and non-technical groups to identify manual processes and provide recommendations for automation, including building models for functions like anomaly detection and case prediction.
  • Full-Lifecycle Ownership: Utilize data engineering skills to integrate and deploy your analytical solutions, ensuring scalability and operational reliability. This includes troubleshooting deployment issues as needed.
  • Collaborate and Communicate: Interface with internal teams and external client stakeholders to effectively communicate technical findings, maintain strong relationships, and ensure delivery aligns with overall objectives.
Minimum Qualifications
  • 5+ years of experience as a Data Scientist.
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences.
  • Proficiency in Python, including libraries for data analysis and modeling.
  • Strong SQL experience to facilitate deep dives and analysis of complex datasets.
  • Strong hands‑on experience with AWS services, Sagemaker, Lambda, Step Functions, Glue, S3, and Athena, used to build and manage production data pipelines.
  • Knowledge of CI/CD pipelines, version control (Git), and Infrastructure-as-Code.
  • Familiarity with logging, monitoring, and alerting using CloudWatch or similar tools.
  • Understanding of IAM roles, policies, and security best practices for AWS services.
  • Curiosity and a passion for exploring data to understand business context and connect technical work to real‑world impact.
  • Willingness to learn new tools/techniques.
Preferred Qualifications
  • Familiarity with AWS Cloud Development Kit (CDK) and/or Typescript.
  • Exceptional comfort with ambiguity and a proven ability to define and drive projects from vague concepts to concrete outcomes.
  • Strong consultative and communication skills, capable of representing the team effectively to clients.
  • Ability to work autonomously in a fully remote, flexible environment.
  • Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM).

Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.

If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.

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